Visual In-Context Prompting
Paper • 2311.13601 • Published • 18
Microsoft Research Papers
#PapersToRead from Microsoft Research in the broad space of Generative AI, Multi-agent systems, responsible AI practices, LLM Ops, and language models
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
Paper • 2308.08155 • Published • 11 -
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models
Paper • 2303.02927 • Published • 3 -
The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4
Paper • 2311.07361 • Published • 14 -
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Paper • 2303.12712 • Published • 5 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 78 -
ToolTalk: Evaluating Tool-Usage in a Conversational Setting
Paper • 2311.10775 • Published • 9 -
GRIM: GRaph-based Interactive narrative visualization for gaMes
Paper • 2311.09213 • Published • 13 -
GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigation
Paper • 2311.07562 • Published • 15 -
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
Paper • 2311.07463 • Published • 14 -
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks
Paper • 2311.06242 • Published • 98 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 52 -
Holistic Evaluation of Text-To-Image Models
Paper • 2311.04287 • Published • 15 -
Leveraging Large Language Models for Automated Proof Synthesis in Rust
Paper • 2311.03739 • Published • 8 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 629 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 92 -
Textbooks Are All You Need
Paper • 2306.11644 • Published • 159 -
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Paper • 2406.12824 • Published • 21 -
Parrot: Efficient Serving of LLM-based Applications with Semantic Variable
Paper • 2405.19888 • Published • 7 -
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Paper • 2310.16427 • Published • 2