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FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 27 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 38 -
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
Collections
Discover the best community collections!
Collections including paper arxiv:2502.08524
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 13 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 54 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 47
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InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU
Paper • 2502.08910 • Published • 139 -
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity
Paper • 2502.13063 • Published • 59 -
Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
Paper • 2502.11089 • Published • 133 -
LLM Pretraining with Continuous Concepts
Paper • 2502.08524 • Published • 26
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 106 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 43 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 29 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 19
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Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
Paper • 2502.03275 • Published • 13 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 114 -
LLM Pretraining with Continuous Concepts
Paper • 2502.08524 • Published • 26
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LLM Pretraining with Continuous Concepts
Paper • 2502.08524 • Published • 26 -
Steel-LLM:From Scratch to Open Source -- A Personal Journey in Building a Chinese-Centric LLM
Paper • 2502.06635 • Published • 4 -
The Curse of Depth in Large Language Models
Paper • 2502.05795 • Published • 31 -
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 190
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Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 114 -
Agency Is Frame-Dependent
Paper • 2502.04403 • Published • 21 -
Distillation Scaling Laws
Paper • 2502.08606 • Published • 43 -
LLM Pretraining with Continuous Concepts
Paper • 2502.08524 • Published • 26
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MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Paper • 2501.02955 • Published • 40 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 99 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 82 -
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos
Paper • 2501.09781 • Published • 25
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 8 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 10 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 58