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How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 18 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 75 -
DragAnything: Motion Control for Anything using Entity Representation
Paper • 2403.07420 • Published • 13 -
Learning and Leveraging World Models in Visual Representation Learning
Paper • 2403.00504 • Published • 31
Collections
Discover the best community collections!
Collections including paper arxiv:2403.15371
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Can large language models explore in-context?
Paper • 2403.15371 • Published • 32 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27 -
CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis
Paper • 2407.13301 • Published • 54 -
WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Paper • 2410.07484 • Published • 48
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Evaluating Very Long-Term Conversational Memory of LLM Agents
Paper • 2402.17753 • Published • 18 -
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
Paper • 2402.16671 • Published • 26 -
Do Large Language Models Latently Perform Multi-Hop Reasoning?
Paper • 2402.16837 • Published • 24 -
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Paper • 2402.15000 • Published • 22
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 49 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 134 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18
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OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Paper • 2402.01739 • Published • 26 -
Rethinking Interpretability in the Era of Large Language Models
Paper • 2402.01761 • Published • 21 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 109 -
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Paper • 2402.07827 • Published • 45
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Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16 -
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation
Paper • 2401.15688 • Published • 11 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 68 -
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities
Paper • 2401.15071 • Published • 34
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Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16 -
Transforming and Combining Rewards for Aligning Large Language Models
Paper • 2402.00742 • Published • 11 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 69 -
Specialized Language Models with Cheap Inference from Limited Domain Data
Paper • 2402.01093 • Published • 45
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PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
Paper • 2402.08714 • Published • 10 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 21 -
RLVF: Learning from Verbal Feedback without Overgeneralization
Paper • 2402.10893 • Published • 10 -
Coercing LLMs to do and reveal (almost) anything
Paper • 2402.14020 • Published • 12
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DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 181 -
Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models
Paper • 2401.04658 • Published • 24 -
Weaver: Foundation Models for Creative Writing
Paper • 2401.17268 • Published • 42 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16