Collections
Discover the best community collections!
Collections including paper arxiv:2406.17245
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Unlocking Continual Learning Abilities in Language Models
Paper • 2406.17245 • Published • 29 -
A Closer Look into Mixture-of-Experts in Large Language Models
Paper • 2406.18219 • Published • 16 -
Symbolic Learning Enables Self-Evolving Agents
Paper • 2406.18532 • Published • 12 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 42
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Unlocking Continual Learning Abilities in Language Models
Paper • 2406.17245 • Published • 29 -
Can Few-shot Work in Long-Context? Recycling the Context to Generate Demonstrations
Paper • 2406.13632 • Published • 5 -
Read Anywhere Pointed: Layout-aware GUI Screen Reading with Tree-of-Lens Grounding
Paper • 2406.19263 • Published • 10 -
Can LLMs Learn by Teaching? A Preliminary Study
Paper • 2406.14629 • Published • 20
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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 • 38 -
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 • 31
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Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 48 -
Better & Faster Large Language Models via Multi-token Prediction
Paper • 2404.19737 • Published • 74 -
ORPO: Monolithic Preference Optimization without Reference Model
Paper • 2403.07691 • Published • 64 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 109
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How to Train Data-Efficient LLMs
Paper • 2402.09668 • Published • 41 -
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Paper • 2403.15042 • Published • 26 -
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets
Paper • 2403.03194 • Published • 14 -
Orca-Math: Unlocking the potential of SLMs in Grade School Math
Paper • 2402.14830 • Published • 24
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 17 -
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 • 70 -
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities
Paper • 2401.15071 • Published • 35
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Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Paper • 2401.10774 • Published • 54 -
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding
Paper • 2401.06761 • Published • 1 -
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache
Paper • 2401.02669 • Published • 14 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 53