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Collections including paper arxiv:2501.03262

FLAME: Factuality-Aware Alignment for Large Language Models

Paper • 2405.01525 • Published May 2, 2024 • 27
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data

Paper • 2405.14333 • Published May 23, 2024 • 38
Transformers Can Do Arithmetic with the Right Embeddings

Paper • 2405.17399 • Published May 27, 2024 • 52
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture

Paper • 2405.18991 • Published May 29, 2024 • 12

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 26
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 13
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 42
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 22

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 146
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20, 2024 • 13
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24, 2024 • 54
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24, 2024 • 47

REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 90

2025 January Papers 🧐

MiniMax-01: Scaling Foundation Models with Lightning Attention

Paper • 2501.08313 • Published Jan 14 • 273
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper • 2501.12948 • Published Jan 22 • 330
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 99
The Lessons of Developing Process Reward Models in Mathematical Reasoning

Paper • 2501.07301 • Published Jan 13 • 91

Reinforce learning 🔃

REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 90
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

Paper • 2412.06531 • Published Dec 9, 2024 • 71
The Differences Between Direct Alignment Algorithms are a Blur

Paper • 2502.01237 • Published 20 days ago • 111
Process Reinforcement through Implicit Rewards

Paper • 2502.01456 • Published 20 days ago • 54

REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 90

RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response

Paper • 2412.14922 • Published Dec 19, 2024 • 86
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

Paper • 2412.17256 • Published Dec 23, 2024 • 46
Deliberation in Latent Space via Differentiable Cache Augmentation

Paper • 2412.17747 • Published Dec 23, 2024 • 30
Outcome-Refining Process Supervision for Code Generation

Paper • 2412.15118 • Published Dec 19, 2024 • 19

STaR: Bootstrapping Reasoning With Reasoning

Paper • 2203.14465 • Published Mar 28, 2022 • 8
Let's Verify Step by Step

Paper • 2305.20050 • Published May 31, 2023 • 10
Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 78
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Paper • 2411.14405 • Published Nov 21, 2024 • 58

Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces

Paper • 2412.14171 • Published Dec 18, 2024 • 24
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 90

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