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Collections including paper arxiv:2501.03262

about 20 hours ago

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

Paper • 2402.04252 • Published Feb 6, 2024 • 28
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 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

about 8 hours ago

Visual-RFT: Visual Reinforcement Fine-Tuning

Paper • 2503.01785 • Published Mar 3 • 76
When an LLM is apprehensive about its answers -- and when its uncertainty is justified

Paper • 2503.01688 • Published Mar 3 • 20
Predictive Data Selection: The Data That Predicts Is the Data That Teaches

Paper • 2503.00808 • Published Mar 2 • 57
Chain of Draft: Thinking Faster by Writing Less

Paper • 2502.18600 • Published Feb 25 • 47

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

Paper • 2501.03262 • Published Jan 4 • 99

Steel-LLM:From Scratch to Open Source -- A Personal Journey in Building a Chinese-Centric LLM

Paper • 2502.06635 • Published Feb 10 • 4
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Paper • 2502.02737 • Published Feb 4 • 223
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 99
MiniMax-01: Scaling Foundation Models with Lightning Attention

Paper • 2501.08313 • Published Jan 14 • 285

2025 January Papers 🧐

MiniMax-01: Scaling Foundation Models with Lightning Attention

Paper • 2501.08313 • Published Jan 14 • 285
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Paper • 2501.12948 • Published Jan 22 • 380
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 107
The Lessons of Developing Process Reward Models in Mathematical Reasoning

Paper • 2501.07301 • Published Jan 13 • 99

Reinforce learning 🔃

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

Paper • 2501.03262 • Published Jan 4 • 99
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

Paper • 2412.06531 • Published Dec 9, 2024 • 72
The Differences Between Direct Alignment Algorithms are a Blur

Paper • 2502.01237 • Published Feb 3 • 115
Process Reinforcement through Implicit Rewards

Paper • 2502.01456 • Published Feb 3 • 60

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

Paper • 2501.03262 • Published Jan 4 • 99
GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training

Paper • 2503.08525 • Published Mar 11 • 15

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

Paper • 2412.14922 • Published Dec 19, 2024 • 89
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

Paper • 2412.17256 • Published Dec 23, 2024 • 48
Deliberation in Latent Space via Differentiable Cache Augmentation

Paper • 2412.17747 • Published Dec 23, 2024 • 33
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 • 82
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Paper • 2411.14405 • Published Nov 21, 2024 • 62

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 • 99

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