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Advances in Cryptology - CRYPTO 2026 - 46th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-20, 2026, Proceedings, Part I
https://doi.org/10.1007/978-3-032-35367-2
[ "Nadia Heninger", "Mike Rosulek" ]
#
CRYPTO2026
Pseudo-Equilibria, Or: How to Stop Worrying About Crypto and Just Analyze the Game
https://doi.org/10.1007/978-3-032-35367-2_1
[ "Alexandros Psomas", "Athina Terzoglou", "Yu Wei", "Vassilis Zikas" ]
#
CRYPTO2026
Security Amplification via Robust Indistinguishability Combiners
https://doi.org/10.1007/978-3-032-35367-2_2
[ "Benny Applebaum", "Nir Bitansky", "Nathan Geier" ]
#
CRYPTO2026
A Unifying Umbrella for Circular-Secure Cryptographic Primitives
https://doi.org/10.1007/978-3-032-35367-2_3
[ "Fuyuki Kitagawa", "Takahiro Matsuda" ]
#
CRYPTO2026
On the Complexity of Interactive Arguments
https://doi.org/10.1007/978-3-032-35367-2_4
[ "Idan Baril", "Iftach Haitner" ]
#
CRYPTO2026
Non-trivial Zero-Knowledge Implies One-Way Functions
https://doi.org/10.1007/978-3-032-35367-2_5
[ "Suvradip Chakraborty", "James Hulett", "Dakshita Khurana", "Kabir Tomer" ]
A recent breakthrough [Hirahara and Nanashima, STOC'2024] established that if $\mathsf{NP} \not \subseteq \mathsf{ioP/poly}$, the existence of zero-knowledge with negligible errors for $\mathsf{NP}$ implies the existence of one-way functions (OWFs). In this work, we obtain a characterization of one-way functions from t...
#
CRYPTO2026
Lower Bounds on Black-Box Constructions of Pseudorandom Functions
https://doi.org/10.1007/978-3-032-35367-2_6
[ "Bar Alon", "Itai Dinur", "Muthuramakrishnan Venkitasubramaniam" ]
In their seminal work, Goldreich, Goldwasser, and Micali [CRYPTO 1984] constructed a pseudorandom function (PRF) using a black-box access to a pseudorandom generator (PRG). When combined with Levin's domain extension technique, the GGM construction invokes the PRG $ω(\log n)$ times, where $n$ denotes the input length t...
#
CRYPTO2026
Unique SNARGs with Adaptive Security: Constructions and Black-Box Separations
https://doi.org/10.1007/978-3-032-35367-2_7
[ "Cody Freitag", "Daniel Wichs" ]
#
CRYPTO2026
Bulletproofs are Optimal: Lower Bounds for Vector Commitments from Fiat-Shamir in Pairing-Free Groups
https://doi.org/10.1007/978-3-032-35367-2_8
[ "Marian Dietz", "Emanuele Giunta" ]
#
CRYPTO2026
Achieving Shannon Capacity for Computationally Bounded Errors
https://doi.org/10.1007/978-3-032-35367-2_9
[ "George Lu", "Jad Silbak", "Daniel Wichs" ]
#
CRYPTO2026
Chosen Ciphertext Secure Pseudorandom Codes in the Standard Model
https://doi.org/10.1007/978-3-032-35367-2_10
[ "Nico Döttling", "Antoine Joux", "Venkata Koppula", "Mahesh Sreekumar Rajasree", "Hendrik Waldner" ]
#
CRYPTO2026
How to Use Polynomially-Hard iO: Turing Machine Obfuscation and More
https://doi.org/10.1007/978-3-032-35367-2_11
[ "Jesko Dujmovic", "Yao-Ching Hsieh", "Abhishek Jain", "Willy Quach" ]
#
CRYPTO2026
Adaptive NIKE for Unbounded Parties
https://doi.org/10.1007/978-3-032-35367-2_12
[ "Shafik Nassar", "Brent Waters" ]
#
CRYPTO2026
Pairing-Based Registered ABE for Boolean Formulas with a Linear-Size CRS
https://doi.org/10.1007/978-3-032-35367-2_13
[ "Roy Stracovsky", "Brent Waters", "David J. Wu" ]
#
CRYPTO2026
Equivocal Broadcast Encryption: Adaptively-Secure Optimal Distributed Broadcast Encryption from Lattices
https://doi.org/10.1007/978-3-032-35367-2_14
[ "Rishab Goyal", "Saikumar Yadugiri" ]
#
CRYPTO2026
Advanced Cryptography from Lattice Isomorphism - New Constructions of IBE and FHE
https://doi.org/10.1007/978-3-032-35367-2_15
[ "Huck Bennett", "Zhengnan Lai", "Noah Stephens-Davidowitz" ]
#
CRYPTO2026
Unbounded Broadcast and KP-ABE with Sublinear Ciphertext from Pairings
https://doi.org/10.1007/978-3-032-35367-2_16
[ "Junichi Tomida", "Hoeteck Wee" ]
#
CRYPTO2026
Collusion-Resistant Constrained PRFs for Compute- &-Compare Predicates from LWE
https://doi.org/10.1007/978-3-032-35367-2_17
[ "Jiaqi Cheng", "Rishab Goyal" ]
#
CRYPTO2026
How to Encrypt with Random Reversible Circuits: Functional, Homomorphic and CCA-Secure
https://doi.org/10.1007/978-3-032-35367-2_18
[ "Ran Canetti", "Ji Luo", "Yiding Zhang" ]
#
CRYPTO2026
Generic-Group Barriers for Function-Hiding and Multi-input Functional Encryption
https://doi.org/10.1007/978-3-032-35367-2_19
[ "Mohammad Hajiabadi", "Roman Langrehr", "Mingyuan Wang" ]
#
CRYPTO2026
Advances in Cryptology - CRYPTO 2026 - 46th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-20, 2026, Proceedings, Part V
https://doi.org/10.1007/978-3-032-35409-9
[ "Nadia Heninger", "Mike Rosulek" ]
#
CRYPTO2026
Cryptomania v.s. Minicrypt in a Quantum World
https://doi.org/10.1007/978-3-032-35409-9_1
[ "Longcheng Li", "Qian Li", "Xingjian Li", "Qipeng Liu" ]
#
CRYPTO2026
Multi-copy Security in Quantum Cryptography and More
https://doi.org/10.1007/978-3-032-35409-9_2
[ "Alper Çakan", "Vipul Goyal", "Fuyuki Kitagawa", "Ryo Nishimaki", "Takashi Yamakawa" ]
#
CRYPTO2026
Constant-Rate Certified Deletion
https://doi.org/10.1007/978-3-032-35409-9_3
[ "Kai-Min Chung", "Tzu-Hsiang Huang", "Wei-Hsiang Hung", "Shota Yamada" ]
#
CRYPTO2026
A Unified Approach to Quantum Key Leasing with a Classical Lessor
https://doi.org/10.1007/978-3-032-35409-9_4
[ "Fuyuki Kitagawa", "Jiahui Liu", "Shota Yamada", "Takashi Yamakawa" ]
#
CRYPTO2026
Less is More: On Copy Complexity in Quantum Cryptography
https://doi.org/10.1007/978-3-032-35409-9_5
[ "Prabhanjan Ananth", "Eli Goldin" ]
#
CRYPTO2026
Anonymous Public-Key Quantum Money and Universally Verifiable Quantum Voting
https://doi.org/10.1007/978-3-032-35409-9_6
[ "Alper Çakan", "Vipul Goyal", "Takashi Yamakawa" ]
#
CRYPTO2026
How to Delete Without a Trace: Certified Deniability in a Quantum World
https://doi.org/10.1007/978-3-032-35409-9_7
[ "Alper Çakan", "Vipul Goyal", "Justin Raizes" ]
#
CRYPTO2026
Scalable, Quantum-Accessible, and Adaptive Pseudorandom Quantum State and Pseudorandom Function-Like Quantum State Generators
https://doi.org/10.1007/978-3-032-35409-9_8
[ "Rishabh Batra", "Zhili Chen", "Rahul Jain", "YaoNan Zhang" ]
We show new constructions for pseudorandom quantum states (PRS) and pseudorandom function-like quantum state (PRFS) generators satisfying scalability, which means the security parameter can be much larger than the number of qubits, quantum accessibility, which means the adversary can provide quantum input, and adaptivi...
#
CRYPTO2026
Uncloneable Cryptography in Linear Quantum Memory
https://doi.org/10.1007/978-3-032-35409-9_9
[ "Andrew Huang", "Omri Shmueli", "Vinod Vaikuntanathan", "Mark Zhandry" ]
#
CRYPTO2026
Separating Non-interactive Classical Verification of Quantum Computation from Falsifiable Assumptions
https://doi.org/10.1007/978-3-032-35409-9_10
[ "Mohammed Barhoush", "Tomoyuki Morimae", "Ryo Nishimaki", "Takashi Yamakawa" ]
Mahadev [SIAM J. Comput. 2022] introduced the first protocol for classical verification of quantum computation based on the Learning-with-Errors (LWE) assumption, achieving a 4-message interactive scheme. This breakthrough naturally raised the question of whether fewer messages are possible in the plain model. Despite ...
#
CRYPTO2026
Unclonable Encryption in the Haar Random Oracle Model
https://doi.org/10.1007/978-3-032-35409-9_11
[ "James Bartusek", "Eli Goldin" ]
We construct unclonable encryption (UE) in the Haar random oracle model, where all parties have query access to $U,U^\dagger,U^*,U^T$ for a Haar random unitary $U$. Our scheme satisfies the standard notion of unclonable indistinguishability security, supports reuse of the secret key, and can encrypt arbitrary-length me...
#
CRYPTO2026
Public-Key Quantum Fire and Key-Fire From Classical Oracles
https://doi.org/10.1007/978-3-032-35409-9_12
[ "Alper Çakan", "Vipul Goyal", "Omri Shmueli" ]
Quantum fire is a distribution of quantum states that can be efficiently cloned, but cannot be efficiently converted into a classical string. First considered by Nehoran and Zhandry (ITCS'24) and later formalized by Bostanci, Nehoran, Zhandry (STOC'25), quantum fire has strong applications and implications in cryptogra...
#
CRYPTO2026
On Scalable Pseudorandom Unitaries and the Unitary Synthesis Problem
https://doi.org/10.1007/978-3-032-35409-9_13
[ "Zvika Brakerski", "Henry Yuen" ]
We consider the task of constructing pseudorandom unitaries (PRUs) with scalable security, i.e. families in which the security parameter may vary independently of the dimension (or input bit-length). It is not known whether scalable PRUs can be constructed. In this work we show that if scalable PRUs can be constructed ...
#
CRYPTO2026
Private Proofs of When and Where
https://doi.org/10.1007/978-3-032-35409-9_14
[ "Uma Girish", "Greg Gluch", "Shafi Goldwasser", "Tal Malkin", "Leo Orshansky", "Henry Yuen" ]
#
CRYPTO2026
Guess-and-Determine Rebound Revisited: Full Quantum Collision Attack on AES-256 in DM Hash Mode
https://doi.org/10.1007/978-3-032-35409-9_15
[ "Liyuan Tang", "Lingyue Qin", "Shiqi Hou", "Xiaoyang Dong" ]
#
CRYPTO2026
Classical and Quantum Full Plaintext Recovery for Low-Round Feistel-Type Designs
https://doi.org/10.1007/978-3-032-35409-9_16
[ "Tingting Guo", "Peng Wang", "Jiwu Jing", "Shuping Mao", "Gang Liu" ]
#
CRYPTO2026
A Geometric Approach to Quantum Distinguishers
https://doi.org/10.1007/978-3-032-35409-9_17
[ "Zhili Wu", "Zhenzhen Bao" ]
#
CRYPTO2026
The Impossibility of Post-quantum Public Indifferentiability for Merkle-Damgård
https://doi.org/10.1007/978-3-032-35409-9_18
[ "Akinori Hosoyamada" ]
#
CRYPTO2026
Advances in Cryptology - CRYPTO 2026 - 46th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 17-20, 2026, Proceedings, Part VII
https://doi.org/10.1007/978-3-032-35415-0
[ "Nadia Heninger", "Mike Rosulek" ]
#
CRYPTO2026
Algebraic Attack on Convolutional Neural Networks with Max Pooling
https://doi.org/10.1007/978-3-032-35415-0_1
[ "Zirui Chen", "Shi Tang", "Zhengchao Gao", "Yongjia Su", "Lingyue Qin", "Xiaoyang Dong" ]
#
CRYPTO2026
Cryptanalytic Extraction of Deep Neural Networks with Non-linear Activations
https://doi.org/10.1007/978-3-032-35415-0_2
[ "Roderick Asselineau", "Patrick Derbez", "Pierre-Alain Fouque", "Brice Minaud" ]
#
CRYPTO2026
Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?
https://doi.org/10.1007/978-3-032-35415-0_3
[ "Akira Ito", "Takayuki Miura", "Yosuke Todo" ]
Deep Neural Networks (DNNs) have attracted significant attention, and their internal models are now considered valuable intellectual assets. Extracting such a model via oracle access to a DNN is conceptually similar to extracting a secret key from a block cipher. Consequently, cryptanalytic techniques, particularly dif...
#
CRYPTO2026
Unforgeable Watermarks for Language Models via Robust Signatures
https://doi.org/10.1007/978-3-032-35415-0_4
[ "Huijia Lin", "Kameron Shahabi", "Min Jae Song" ]
#
CRYPTO2026
A Little LESS Secure - Side-Channel Attacks Exploiting Randomness Leakage
https://doi.org/10.1007/978-3-032-35415-0_5
[ "Dina Hesse", "Elisabeth Krahmer", "Yi-Fu Lai", "Jonas Meers" ]
#
CRYPTO2026
Maskaglia: A New, Efficient Approach to Masked Discrete Gaussian Sampling
https://doi.org/10.1007/978-3-032-35415-0_6
[ "Calvin Abou Haidar", "Thomas Espitau", "Clément Hoffmann", "Mehdi Tibouchi" ]
#
CRYPTO2026
Robust Single-Trace Full-Key Extraction from Million-Point Traces With Cross-Implementation Transfer
https://doi.org/10.1007/978-3-032-35415-0_7
[ "Aron Gohr", "Friederike Laus", "Gregor Leander" ]
#
CRYPTO2026
Bypassing the Random-Probing Model in Masking Security Proofs
https://doi.org/10.1007/978-3-032-35415-0_8
[ "Julien Béguinot", "Gianluca Brian", "Loïc Masure" ]
#
CRYPTO2026
Leakage-Tolerant Circuits Against sfAC0 Leakage
https://doi.org/10.1007/978-3-032-35415-0_9
[ "Yaohua Ma", "Yifan Song" ]
#
CRYPTO2026
Secure Computation Against NC1 Leakage Without Secure Hardware
https://doi.org/10.1007/978-3-032-35415-0_10
[ "Yuyu Wang" ]
#
CRYPTO2026
A Formal Security Proof of Masking - Reduction from Strong Noisy Leakage to Probing Model Without Random Probing and Application to LR Primitive
https://doi.org/10.1007/978-3-032-35415-0_11
[ "Rei Ueno", "Akiko Inoue", "Kazuhiko Minematsu", "Akira Ito", "Naofumi Homma" ]
#
CRYPTO2026
Generic-Compatible Distinguishers for Linear Regression Based Attacks
https://doi.org/10.1007/978-3-032-35415-0_12
[ "Sana Boussam" ]
#
CRYPTO2026
Playing Tag with Okamoto-Schnorr: Three-Move Pairing-Free Blind Signatures from DDH
https://doi.org/10.1007/978-3-032-35415-0_13
[ "Rutchathon Chairattana-Apirom", "Michael Reichle", "Stefano Tessaro" ]
#
CRYPTO2026
Blind Signatures from Arguments of Inequality
https://doi.org/10.1007/978-3-032-35415-0_14
[ "Michael Klooß", "Russell W. F. Lai", "Michael Reichle" ]
#
CRYPTO2026
Improved Concurrent-Secure Blind Schnorr Signatures
https://doi.org/10.1007/978-3-032-35415-0_15
[ "Pierpaolo Della Monica", "Ivan Visconti" ]
#
CRYPTO2026
On the Impossibility of Round-Optimal Pairing-Free Blind Signatures in the ROM
https://doi.org/10.1007/978-3-032-35415-0_16
[ "Marian Dietz", "Julia Kastner", "Stefano Tessaro" ]
#
CRYPTO2026
Round-Optimal GUC-Secure Blind Signatures From Minimal Computational and Setup Assumptions - From Minimal Computational and Setup Assumptions
https://doi.org/10.1007/978-3-032-35415-0_17
[ "Michele Ciampi", "Pierpaolo Della Monica", "Ivan Visconti" ]
#
CRYPTO2026
Round-Optimal Threshold Blind Signatures Without Random Oracles
https://doi.org/10.1007/978-3-032-35415-0_18
[ "Georg Fuchsbauer", "Fabian Regen", "Hoeteck Wee" ]
#
CRYPTO2026
Three-Move Blind Signatures in Pairing-Free Groups
https://doi.org/10.1007/978-3-032-35415-0_19
[ "Yanbo Chen" ]
#
CRYPTO2026
Proceedings of the ACM SIGCOMM 2026 Conference, SIGCOMM 2026, Colorado Convention Center, Denver, CO, USA, August 17-21, 2026
https://doi.org/10.1145/3789240
[ "Eric Keller", "Sangtae Ha", "Laurent Vanbever", "Theophilus Benson" ]
#
SIGCOMM2026
KVServe: Service-Aware KV Cache Compression for Communication-Efficient Disaggregated LLM Serving
https://doi.org/10.1145/3789240.3829139
[ "Zedong Liu", "Xinyang Ma", "Dejun Luo", "Hairui Zhao", "Bing Lu", "Wenjing Huang", "Yida Gu", "Xingchen Liu", "Zheng Wei", "Jinyang Liu", "Dingwen Tao", "Guangming Tan" ]
LLMs are widely adopted in production, pushing inference systems to their limits. Disaggregated LLM serving (e.g., PD separation and KV state disaggregation) improves scalability and cost efficiency, but it also turns KV into an explicit payload crossing network and storage boundaries, making KV a dominant end-to-end b...
#
SIGCOMM2026
DualPath: Accelerating Agentic LLM Inference by Harvesting Disaggregated KV-Cache Storage I/O
https://doi.org/10.1145/3789240.3829159
[ "Yongtong Wu", "Shaoyuan Chen", "Rilin Huang", "Yixuan Tan", "Yinmin Zhong", "Mingxing Zhang", "Xin Jin", "Panpan Huang" ]
The performance of multi-turn, agentic LLM inference is increasingly dominated by KV-Cache storage I/O rather than computation. In prevalent disaggregated architectures, loading the massive KV-Cache from external storage creates a fundamental imbalance: storage NICs on prefill engines become bandwidth-saturated, while ...
#
SIGCOMM2026
Efficient Remote KV Cache Reuse with GPU-native Video Codec
https://doi.org/10.1145/3789240.3829120
[ "Liang Mi", "Weijun Wang", "Jinghan Chen", "Ting Cao", "Haipeng Dai", "Yunxin Liu" ]
Remote KV cache reuse fetches KV cache for identical contexts from remote storage, avoiding recomputation, accelerating LLM inference. While it excels in high-speed networks, its performance degrades significantly in bandwidth-limited scenarios. Recent studies address this by transmitting KV caches in compressed form, ...
#
SIGCOMM2026
Connex: Endpoint Mobility Primitives for Dynamic LLM Serving
https://doi.org/10.1145/3789240.3829200
[ "Yanying Lin", "Vincent Liu", "Tao Luo", "ChengZhong Xu", "Kejiang Ye" ]
Modern LLM serving systems increasingly adopt elastic inference pipelines where stages frequently join, leave, and migrate across nodes. However, existing GPU communication frameworks like NCCL assume static topologies, causing routing failures and P99 latency spikes during worker transitions that violate sub-milliseco...
#
SIGCOMM2026
TurboBus: Pooling PCIe Bandwidth for LLM Workloads via Scale-Up Fabrics
https://doi.org/10.1145/3789240.3829130
[ "Xinyu Yang", "Kaiqiang Xu", "Kai Chen" ]
GPU memory offloading is widely adopted for LLM workloads but shifts the bottleneck to GPU-CPU transfers, which can take up to 90% of the end-to-end inference/training time! Paradoxically, over 60% of PCIe bandwidth remains idle. The root cause is that PCIe links are individually bottlenecked but collectively underutil...
#
SIGCOMM2026
Towards Efficient Verification of Distributed In-Network Computing Programs
https://doi.org/10.1145/3789240.3829122
[ "Mingyuan Song", "Huan Shen", "Jinghui Jiang", "Qiang Su", "Ziheng Zhang", "Qingyu Song", "Yuchao Zhang", "Wanjian Feng", "Fei Yuan", "Yitao Xing", "Wenjia Wei", "Qiao Xiang", "Jiwu Shu" ]
Distributed in-network programs are increasingly deployed in data centers for their performance benefits, but shifting application logic to switches also enlarges the failure domain. Ensuring their correctness before deployment is thus critical for reliability. While prior verification frameworks can efficiently verify...
#
SIGCOMM2026
When static verification is not enough: revealing BGP bugs at runtime
https://doi.org/10.1145/3789240.3829137
[ "Pietro Ronchetti", "Tibor Schneider", "Laurent Vanbever" ]
Operators go to great lengths to ensure their BGP networks are correct. Yet, despite their efforts, faults still happen due to software or hardware bugs which can often have detrimental network-wide consequences. Today, all operators can do is react to such failures, often only once it is already too late. We present G...
#
SIGCOMM2026
Explainable Network Verification via Localized Subspecification
https://doi.org/10.1145/3789240.3829155
[ "Yongzheng Zhang", "Yaxuan Lin", "Haoxian Chen", "Ruize Ma", "Amirmohammad Nazari", "Mukund Raghothaman", "Peng Zhang" ]
Network verification, synthesis, and repair tools help enforce high-level operational intent, but their limited explainability makes configuration maintenance costly in practice, as operators must still manually reason about large, low-level configurations. We propose localized subspecifications, which explain how indi...
#
SIGCOMM2026
VeriLucid: A Verification-aware Data-plane Programming Language
https://doi.org/10.1145/3789240.3829171
[ "John Sonchack", "Pamela Zave", "Jennifer Rexford" ]
Correctness is important in data-plane programs, which run on critical infrastructure connecting millions of users. Verification helps programmers build correct software, but current data-plane tools can only check simple properties or require immense programmer effort. As a solution, this paper introduces the first ve...
#
SIGCOMM2026
Elastispec: Formalizing Enterprise Firewall Management with Informal and Elastic Specifications
https://doi.org/10.1145/3789240.3829191
[ "Chenan Wen", "Yizhan Qing", "Curt P. Jansen", "Xiaokang Qiu", "Sanjay G. Rao" ]
Managing enterprise network firewalls is an ad-hoc process today, where administrators must extract policies relevant to their enterprises from thousands of natural language vendor documents and tailor them to their unique context. In this paper, we present Elastispec, a first step towards principled management of ente...
#
SIGCOMM2026
Trivance: Latency-Optimal AllReduce by Shortcutting Multiport Networks
https://doi.org/10.1145/3789240.3829181
[ "Anton Juerss", "Vamsi Addanki", "Stefan Schmid" ]
AllReduce is a fundamental collective communication operation in distributed computing and a key performance bottleneck for large-scale training and inference. Its completion time is determined by the number of communication steps, which dominate latency-sensitive workloads, and the communication distance affecting bot...
#
SIGCOMM2026
OptCCL: Scalable Synthesis of Optimal Collective Communication Algorithms
https://doi.org/10.1145/3789240.3829207
[ "Richard Shapley", "Rachit Agarwal", "David B. Shmoys" ]
We present OptCCL, a technique to synthesize collective communication algorithms that are optimal for a given host and network hardware and topology. OptCCL is general: it enables synthesizing optimal algorithms for all existing collectives, for all existing hardware, and even for multiple concurrent collectives sharin...
#
SIGCOMM2026
DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce
https://doi.org/10.1145/3789240.3829148
[ "Wenchen Han", "Shay Vargaftik", "Michael Mitzenmacher", "Ran Ben Basat" ]
Multi-hop all-reduce is the de facto backbone of large model training. As the training scale increases, the network often becomes a bottleneck, motivating the reduction of the volume of transmitted data. Accordingly, recent systems have demonstrated significant acceleration of the training process using gradient quanti...
#
SIGCOMM2026
ZipCCL: Efficient Lossless Data Compression of Communication Collectives for Accelerating LLM Training
https://doi.org/10.1145/3789240.3829204
[ "Wenxiang Lin", "Xinglin Pan", "Ruibo Fan", "Shaohuai Shi", "Xiaowen Chu" ]
Communication has emerged as a critical bottleneck in the distributed training of large language models (LLMs). While numerous approaches have been proposed to reduce communication overhead, the potential of lossless compression has remained largely underexplored since compression and decompression typically consume la...
#
SIGCOMM2026
Theseus: Runtime-Adaptive GPU Collective Communication with Hot-Swappable Schedules
https://doi.org/10.1145/3789240.3829134
[ "Rui Ding", "Xiandong Lu", "Jiajun Wang", "Xunpeng Liu", "Feiyang Wang", "Xuran Hao", "Houyuan Zhu", "Anyi Xu", "Sinuo Cao", "Haifeng Sun", "Qun Huang", "Jiamin Cao", "Jiaqi Gao" ]
Current GPU Collective Communication Libraries (CCLs) employ predefined schedules optimized for stable environments. Their supported schedules and selection logic are fixed at communicator initialization, which fails to account for evolving runtime conditions, such as workload characteristics and hardware health status...
#
SIGCOMM2026
CausalTune: Causal Learning based Automated Cellular RAN Configuration Tuning Framework
https://doi.org/10.1145/3789240.3829109
[ "Leyang Xue", "Bolun Zhang", "Yibo Ma", "Mahesh K. Marina", "He Yan", "Yu Zhou", "Cheuk Yiu Ip", "Senthil Dhandapani", "James Klosowski" ]
Continual configuration tuning in cellular radio access networks (RANs) is critical for maintaining performance, reliability, energy efficiency, and user experience. However, this task remains largely manual in practice. Automating it needs to confront high-dimensional configuration spaces, sparse and biased exploratio...
#
SIGCOMM2026
SAGE: A Real-Time AI System for Reducing Latency in NextG Cellular Networks
https://doi.org/10.1145/3789240.3829112
[ "Aoyu Gong", "Raphael Cannatà", "Arman Maghsoudnia", "Néstor Lomba Lomba", "Dan Mihai Dumitriu", "Haitham Hassanieh" ]
NextG applications such as AR/VR, industrial automation, cloud gaming, and autonomous robots increasingly demand lower latencies. Current 5G networks, however, incur significant delays due to request-based scheduling, where users must signal demand before the base station can allocate resources for uplink transmissions...
#
SIGCOMM2026
RANPilot: Making AI Functionalities Robust to Dynamic O-RAN Reconfigurations
https://doi.org/10.1145/3789240.3829146
[ "Shiming Yu", "Leming Shen", "Jianing Zhang", "Xin Li", "Xianjin Xia", "Yuanqing Zheng", "Yaxiong Xie" ]
The Open Radio Access Network (O-RAN) promises unprecedented flexibility through its reconfigurable architecture and AI-driven control. However, this agility exposes a critical fragility: AI models trained on one network configuration suffer significant performance degradation after an upgrade due to dramatic data drif...
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SIGCOMM2026
Synchronizing with the Scheduler: Dual-Loop Congestion Control for 5G Uplink on Commodity Devices
https://doi.org/10.1145/3789240.3829199
[ "Qiang Wu", "Yuxin Liu", "Tianyang Zhang", "Haoran Wan", "Kyle Jamieson", "Yaxiong Xie" ]
Current end-to-end congestion-control feedback is too slow to track rapid wireless dynamics in cellular networks. We identify Grant-to-Buffer Ratio (GBR)—the ratio of base-station uplink grants to mobile-reported demand—as a millisecond-scale RAN signal of uplink resource scarcity. Measurements across AT&T, Verizon, an...
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SIGCOMM2026
Unveiling Low‑Altitude 5G Performance: Linking Key Influencing Factors with UAV Flight Parameters
https://doi.org/10.1145/3789240.3829198
[ "Xinzhe Liu", "Jianer Zhou", "Xiaoyong Ni", "Ke Luo", "Zhenyu Li", "Xiaofeng Tao", "Weichao Li" ]
Although 5G is widely regarded as a key technology for unmanned aerial vehicle (UAV) cellular communications, its practical performance in low-altitude scenarios remains insufficiently understood. To address this, we conduct large-scale flight measurements over commercial 5G networks and build a cross-layer dataset to ...
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SIGCOMM2026
Turbo: Efficiently Serving Long-Context Large Language Models with In-Network Aggregation
https://doi.org/10.1145/3789240.3829140
[ "Ying Wan", "Yuchen Xu", "Chuwen Zhang", "Yingsheng Huang", "Yong Feng", "Wenquan Xu", "Jialin Li", "Mingwei Xu", "Wenfei Wu", "Congcong Miao" ]
LLM supporting long contexts faces a critical memory bottleneck due to the linear growth of KV cache. Distributing the storage across multiple GPUs alleviates this burden but introduces significant communication overhead or traffic incast, especially during the decoding phase. We propose Turbo, a first-of-its-kind in-n...
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SIGCOMM2026
HyNA: Taming Tail Latency in MoE Training with Hybrid Switch Silicon
https://doi.org/10.1145/3789240.3829178
[ "Yang Liu", "Tianxiang Liu", "Haipeng Yao" ]
The transition to trillion-parameter models, particularly Mixture-of-Experts (MoE), shifts the bottleneck of distributed training from computation to communication. However, existing Parameter Server (PS) architectures succumb to incast congestion, while state-of-the-art In-Network Aggregation (INA) solutions like ATP ...
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SIGCOMM2026
EPIC: Abstraction and Polymorphism of In-Network Collectives on Ethernet
https://doi.org/10.1145/3789240.3829196
[ "Yitao Yuan", "Jianglong Nie", "Tianyu Bai", "Ruizhe Zhou", "Siyuan Cao", "Xujie Fan", "Yuchen Xu", "Junkai Chen", "Chenqi Zhao", "Nengyuan Zhang", "Shaoke Fang", "Jiangyuan Chen", "Yuanfeng Chen", "Jiaqi Sun", "Zhan Wang", "Xiaohua Xu", "Yuchao Zhang", "Yang Liu", "Xiangrui Yang...
In-Network Collective (INC) acceleration holds immense potential for optimizing AI training and inference; however, its cross-layer nature has historically hindered investment and adoption within the open Ethernet ecosystem. To bridge this gap, we propose EPIC (Ethernet Polymorphic In-network Collectives), an INC proto...
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SIGCOMM2026
PReCCL: Performant and Resilient Collective Communication via Integrated Inband Telemetry and Workload Reallocation
https://doi.org/10.1145/3789240.3829133
[ "Zhiyong Chen", "Kaihui Gao", "Li Chen", "Rui Yan", "Zihan Yan", "Fei Gui", "Dan Li", "Jiamin Cao", "Jiaqi Gao" ]
Modern collective communication libraries (CCLs) execute a collective communication task (CCT) by decomposing it into multiple sub-tasks, each mapped to a specific Virtual Topology (VT), which is an ordered graph of GPUs (e.g., a ring or a tree), to maximize parallelism and link utilization. As AI training scales to la...
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SIGCOMM2026
UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods
https://doi.org/10.1145/3789240.3829183
[ "Yipeng Liu", "Chang Liu", "Si Shen", "Jiaqi Zheng", "Mingfan Li", "Yuyang Yang", "Guanhua Li", "Yuquan Zhang", "Yimeng Xu", "Zhongzhe Hu", "Zhiyuan Huang", "Qihang Duan", "Junsong Wang", "Wenkai Ling", "Baochuan Yang", "Xianzhi Yu", "Han Bao", "Yijie Chen", "Guihai Chen" ]
The deployment of Mixture-of-Experts (MoE) models on production high-bandwidth superpods, such as NVIDIA's NVL72/576 and Huawei's CloudMatrix384, introduces critical challenges beyond raw interconnect bandwidth. While these systems provide unified global address spaces and high-bandwidth fabrics, their full potential f...
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SIGCOMM2026
Dorado: Scaling SmartNIC Session Tables on Commodity DDRs
https://doi.org/10.1145/3789240.3829121
[ "Heng Yu", "Kai Ren", "Jiajun Liang", "Baozeng Zhang", "Guozhi Lin", "Xinyi Zhang", "Jian Wang", "Jian Zhao", "Ziyue Zhai", "Liang Wang", "Chao Pei", "Jilong Wang", "Gaogang Xie", "Ang Chen", "Congcong Miao" ]
FPGA-based SmartNICs are widely deployed for cloud network function acceleration, but their memory subsystem is under increasing pressure because of large session tables. Conventional wisdom suggests that high packet processing performance relies on advanced memories (e.g., SRAM, HBM), but those are costly to add at cl...
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SIGCOMM2026
XFir: Accelerating New-Flow Setup on Host Servers of a Large Cloud Network
https://doi.org/10.1145/3789240.3829131
[ "Shihan Lin", "Shunqiao Jiang", "Liang Wang", "Jian Wang", "Chao Pei", "Jian Zhao", "Wenjun Wu", "Kai Ren", "Lijun Zhuang", "Qingmin Liu", "Heng Yu", "Sirui Li", "Yibo Huang", "Yifei Zhu", "Yunming Xiao", "Ang Chen", "Linghe Kong", "Congcong Miao" ]
In today's cloud networks, host servers widely deploy Data Processing Units (DPUs) as network accelerators under the "Sep-Path" paradigm. However, as server capabilities scale with increasing CPU cores and network bandwidth, the software slow path (executed on a DPU's CPU) has become a critical bottleneck for workloads...
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SIGCOMM2026
FlowTurbo: From Best-Effort to Hit-Driven MegaFlow Hardware Offloading in Open vSwitch
https://doi.org/10.1145/3789240.3829138
[ "Zhongxian Liang", "Sheng Lan", "Ying Li", "Zihan Li", "Wenjun Li", "Yao Xin", "Han Wang", "Tong Yang", "Yu Zhang", "Gaogang Xie", "Bin Liu", "Weizhe Zhang" ]
Offloading fast-path MegaFlows in Open vSwitch to hardware accelerators is a common approach for accelerating packet forwarding in modern cloud data centers. However, due to the limited capabilities of current hardware accelerators, existing solutions still rely on coarse-grained, best-effort offloading, which struggle...
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SIGCOMM2026
CubeTrace: Microscopic Network Tracing for Heterogeneous Cloud Gateways
https://doi.org/10.1145/3789240.3829165
[ "Yunming Xiao", "Yinchao Yang", "Jiaqi Zheng", "Xuqian Li", "Dongbo Gu", "Jun Zhang", "Miantao Wan", "Chao Pei", "Chen Tian", "Mingwei Xu", "Ang Chen", "Congcong Miao" ]
Modern cloud gateways have evolved to include diverse network functions and heterogeneous hardware, such as programmable switches and FPGAs, to handle increasing workloads and minimize forwarding latency. Existing network tracing tools, however, operate primarily at device granularity and cannot pinpoint which function...
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SIGCOMM2026
Rethinking Cloud Optimization: Volatility-Driven for Better Outcomes
https://doi.org/10.1145/3789240.3829141
[ "Baoqing Wang", "Gongming Zhao", "Hongli Xu", "Shibo Wu", "Zhuolong Yu", "Jiawei Liu", "Junhong Lu", "Shaohui Xu", "Fanjie Meng" ]
Cloud providers commonly employ oversubscription strategies to maximize profitability, leveraging the significant gap between the resources purchased by tenants and those actually consumed by their workloads. However, the temporal volatility of workloads may lead to overload on oversubscribed nodes. To address this iss...
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SIGCOMM2026
Connecting 100K+ GPUs: Building the Communication Stack for Large-Scale LLM Training
https://doi.org/10.1145/3789240.3829152
[ "Hongyi Zeng", "Min Si", "Pavan Balaji", "Yongzhou Chen", "Ching-Hsiang Chu", "Adithya Gangidi", "Prashanth Kannan", "Bingzhe Liu", "Saif Hasan", "Dong He", "Deep Shah", "Ashmitha Jeevaraj Shetty", "Gregory R. Steinbrecher", "Srikanth Sundaresan", "Yulun Wang", "Yexin Wu", "Mingran Y...
The arrival of 100K+ GPU clusters marks a new frontier in AI infrastructure. Standard communication stack meets new challenges as physical topologies span multiple datacenter buildings, introducing high bandwidth-delay product links where latency increases by up to 30× compared to intra-rack traffic. Furthermore, the t...
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SIGCOMM2026
DistDPU: A Disaggregated DPU Architecture for High-Performance and Cost-Efficient AI Clouds
https://doi.org/10.1145/3789240.3829161
[ "Hao Mei", "Lizhou Gao", "Yuanyi Zhu", "Liang Wang", "Peng Yang", "Chao Pei", "Chuhao Chen", "Zijian Li", "Jian Zhao", "Dongbo Gu", "Hongchen Ren", "Jiyuan Chen", "Junpeng Zhang", "Yunpeng Guan", "Jianye Yuan", "Jian Wang", "Yibo Huang", "Yang Xu" ]
AI training and inference are driving cloud networks toward terabit-per-second (Tbps) bandwidth per server, challenging the scalability and efficiency of today's cloud network architectures. A prevalent design scales bandwidth by stacking monolithic Data Processing Units (DPUs), but this approach tightly couples contro...
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SIGCOMM2026
Pegasus: A Data Center Network for Bare-Metal AI Cloud
https://doi.org/10.1145/3789240.3829186
[ "Xianneng Zou", "Yadong Liu", "Yiran Zhang", "Jian Zhao", "Zhaoxun Zhou", "Qing Wang", "Xingyi Li", "Liang Wang", "Xingda Wei", "Xiaojie Huang", "Zhaohe Chen", "Yinben Xia", "Yuxi Wang", "Kai Ren", "Lizhou Gao", "Jiajun Liang", "Jian Wang", "Chunxu Zhao", "Weifeng Zhang", "Lu S...
Today, AI cloud is key to serving diverse users with AI services, where cloud networking forms the basis. In this paper, we share our experience in designing, deploying, and operating Pegasus, a data center network tailored for the AI cloud, along with operational lessons learned from its deployment. The key designs of...
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SIGCOMM2026
Balancing and Beyond: Communication-Centric Optimizations in Expert Parallelism
https://doi.org/10.1145/3789240.3829201
[ "Jiamin Cao", "Qingxu Li", "Yaozhong Liu", "Jiaqi Gao", "Yan Zhang", "Shangfeng Shi", "Zian Chen", "Yizhi Wang", "Jun Zhang", "Kunling He", "Ennan Zhai", "Jianbo Dong", "Binzhang Fu", "Dennis Cai" ]
The Mixture-of-Experts (MoE) architecture scales large language models (LLMs) to trillions of parameters by activating only a small subset of experts per token. In practice, MoE inference is commonly deployed with Expert Parallelism (EP), which places whole experts on different GPUs to preserve kernel efficiency. Howev...
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SIGCOMM2026
FlowForm: Scalable Passive Metasurface Network for mmWave Coverage Expansion
https://doi.org/10.1145/3789240.3829102
[ "Wuqiong Zhao", "Baicheng Chen", "Kai Zheng", "Xingyu Chen", "Wenqian Zhang", "Xinyu Zhang" ]
Millimeter wave (mmWave) networks offer multi-gigabit data rates but suffer from severe path loss and blockage, resulting in spotty coverage. Emerging reconfigurable intelligent surfaces (RIS) can mitigate these challenges, but their reliance on active control channels, power sources, and complex runtime coordination i...
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SIGCOMM2026
Concurrent OFDM Backscatter with a Single Commercial Receiver
https://doi.org/10.1145/3789240.3829127
[ "Caihui Du", "Jihong Yu", "Rongrong Zhang" ]
Concurrent OFDM backscatter is promising for enabling efficient connectivity of soaring ultra-low power IoT devices. However, the existing designs rely on frequency-domain division, suffering from short synchronization distance, poor interference robustness and incompatibility with commercial Wi-Fi receivers. We presen...
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SIGCOMM2026
Deep-Soil Acoustic Backscatter Networking for Electrical Substation Grounding Assessment
https://doi.org/10.1145/3789240.3829168
[ "Fengrui Zhang", "Shanyue Wang", "Bowen Xue", "Lei Yang" ]
Electrical substation grounding integrity is fundamental to power system safety, yet its long-term performance is strongly influenced by soil conditions that are difficult to monitor continuously. Existing underground sensing approaches are largely ineffective due to severe signal attenuation in soil, strong electromag...
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SIGCOMM2026
Concord: Airtime-Aware Contention Control for Taming Tail Latency from Wi-Fi Frame Bursting
https://doi.org/10.1145/3789240.3829149
[ "Fengqian Guo", "Siqi Wei", "Sihao Miao", "Xinle Du", "Hancheng Lu" ]
In congested Wi-Fi, sending less does not guarantee lower latency. Based on measurements on commodity Wi-Fi routers in the wild, sparse microflows can suffer bulk-like tail latency even at negligible load. This latency is driven by MAC-level contention dynamics rather than a flow's sending rate, rendering rate-based co...
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SIGCOMM2026
LITE: Loss-resilient Immersive Telepresence with Multi-modal Semantics
https://doi.org/10.1145/3789240.3829116
[ "Ruizhi Cheng", "Harshvardhan Takawale", "Nan Wu", "Nirupam Roy", "Sennur Ulukus", "Matteo Varvello", "Eugene Chai", "Bo Han" ]
Immersive telepresence has the potential to transform real-time communication through highly interactive and engaging experiences. Despite recent advances in reducing communication and computation costs, existing systems largely overlook packet loss, which can severely degrade the quality of experience (QoE). Recoverin...
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SIGCOMM2026
FabricPerf: Measuring NIC-less Scale-Up Network through GPU Communication Kernel Profiling
https://doi.org/10.1145/3789240.3829172
[ "Songlin Huang", "Chenshu Wu" ]
The rapid growth of distributed machine learning systems shifts ML networks from the CPU/GPU-NIC to GPU-Fabrics architectures, creating an emerging need to measure and optimize NIC-less Scale-up networks. Yet, the disappearance of NICs removes key observability points and leaves existing measurement tools largely limit...
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SIGCOMM2026
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