-
PDFTriage: Question Answering over Long, Structured Documents
Paper • 2309.08872 • Published • 53 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 39 -
Context-Aware Meta-Learning
Paper • 2310.10971 • Published • 16
Collections
Discover the best community collections!
Collections including paper arxiv:2406.09170
-
Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs
Paper • 2407.00653 • Published • 11 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 40 -
Whiteboard-of-Thought: Thinking Step-by-Step Across Modalities
Paper • 2406.14562 • Published • 27 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27
-
CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery
Paper • 2406.08587 • Published • 15 -
Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning
Paper • 2406.09170 • Published • 24 -
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents
Paper • 2407.18901 • Published • 31 -
Benchmarking Agentic Workflow Generation
Paper • 2410.07869 • Published • 25
-
Compression Represents Intelligence Linearly
Paper • 2404.09937 • Published • 27 -
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Paper • 2404.06395 • Published • 21 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 35 -
Are large language models superhuman chemists?
Paper • 2404.01475 • Published • 16
-
GAIA: a benchmark for General AI Assistants
Paper • 2311.12983 • Published • 183 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35 -
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
RULER: What's the Real Context Size of Your Long-Context Language Models?
Paper • 2404.06654 • Published • 33
-
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 47 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 19 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602