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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 22 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 145 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2409.04109
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SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
Paper • 2409.05556 • Published • 2 -
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Paper • 2409.04109 • Published • 43 -
A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?
Paper • 2409.15277 • Published • 35 -
Learning Task Decomposition to Assist Humans in Competitive Programming
Paper • 2406.04604 • Published • 4
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 52 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 30 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 106 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 26
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Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Paper • 2409.04109 • Published • 43 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 136 -
Reward-Robust RLHF in LLMs
Paper • 2409.15360 • Published • 6 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 26
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Can Large Language Models Unlock Novel Scientific Research Ideas?
Paper • 2409.06185 • Published • 12 -
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Paper • 2409.04109 • Published • 43 -
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
Paper • 2408.06292 • Published • 118
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SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Paper • 2408.15545 • Published • 34 -
InkubaLM: A small language model for low-resource African languages
Paper • 2408.17024 • Published • 12 -
From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Paper • 2409.03512 • Published • 27 -
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Paper • 2409.04109 • Published • 43
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Large Language Model Unlearning via Embedding-Corrupted Prompts
Paper • 2406.07933 • Published • 7 -
Block Transformer: Global-to-Local Language Modeling for Fast Inference
Paper • 2406.02657 • Published • 37 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 19 -
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 30
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FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 24 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 37 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 52 -
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
Paper • 2405.18991 • Published • 12
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Can large language models explore in-context?
Paper • 2403.15371 • Published • 32 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 44 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 36 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 60