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Collections including paper arxiv:2406.02900

mDPO: Conditional Preference Optimization for Multimodal Large Language Models

Paper • 2406.11839 • Published Jun 17 • 36
Pandora: Towards General World Model with Natural Language Actions and Video States

Paper • 2406.09455 • Published Jun 12 • 14
WPO: Enhancing RLHF with Weighted Preference Optimization

Paper • 2406.11827 • Published Jun 17 • 14
In-Context Editing: Learning Knowledge from Self-Induced Distributions

Paper • 2406.11194 • Published Jun 17 • 15

Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?

Paper • 2406.04391 • Published Jun 6 • 6
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Paper • 2406.02900 • Published Jun 5 • 10

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Paper • 2406.06525 • Published Jun 10 • 64
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning

Paper • 2406.06469 • Published Jun 10 • 23
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Paper • 2406.04271 • Published Jun 6 • 27
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published Jun 4 • 36

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Paper • 2406.02900 • Published Jun 5 • 10

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Paper • 2406.02900 • Published Jun 5 • 10
Building Math Agents with Multi-Turn Iterative Preference Learning

Paper • 2409.02392 • Published 23 days ago • 14

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Paper • 2406.02900 • Published Jun 5 • 10

Understanding the performance gap between online and offline alignment algorithms

Paper • 2405.08448 • Published May 14 • 14
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment

Paper • 2405.19332 • Published May 29 • 15
Offline Regularised Reinforcement Learning for Large Language Models Alignment

Paper • 2405.19107 • Published May 29 • 13
Show, Don't Tell: Aligning Language Models with Demonstrated Feedback

Paper • 2406.00888 • Published Jun 2 • 30

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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 26
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24 • 12
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20 • 45
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 28

ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12 • 60
sDPO: Don't Use Your Data All at Once

Paper • 2403.19270 • Published Mar 28 • 38
Teaching Large Language Models to Reason with Reinforcement Learning

Paper • 2403.04642 • Published Mar 7 • 46
Best Practices and Lessons Learned on Synthetic Data for Language Models

Paper • 2404.07503 • Published Apr 11 • 29

Secrets of RLHF in Large Language Models Part II: Reward Modeling

Paper • 2401.06080 • Published Jan 11 • 24
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

Paper • 2406.02900 • Published Jun 5 • 10
AgentGym: Evolving Large Language Model-based Agents across Diverse Environments

Paper • 2406.04151 • Published Jun 6 • 17
Understanding and Diagnosing Deep Reinforcement Learning

Paper • 2406.16979 • Published Jun 23 • 9

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