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Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 59 -
CRAG -- Comprehensive RAG Benchmark
Paper • 2406.04744 • Published • 48 -
Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach
Paper • 2406.04594 • Published • 8 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 30
Collections
Discover the best community collections!
Collections including paper arxiv:2405.19332
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Understanding the performance gap between online and offline alignment algorithms
Paper • 2405.08448 • Published • 19 -
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Paper • 2405.19332 • Published • 22 -
Offline Regularised Reinforcement Learning for Large Language Models Alignment
Paper • 2405.19107 • Published • 15 -
Show, Don't Tell: Aligning Language Models with Demonstrated Feedback
Paper • 2406.00888 • Published • 33
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AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets
Paper • 2404.05623 • Published • 3 -
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Paper • 2405.19332 • Published • 22 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7 -
Deep Bayesian Active Learning for Preference Modeling in Large Language Models
Paper • 2406.10023 • Published • 2
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Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 59 -
CRAG -- Comprehensive RAG Benchmark
Paper • 2406.04744 • Published • 48 -
Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach
Paper • 2406.04594 • Published • 8 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 30
-
Understanding the performance gap between online and offline alignment algorithms
Paper • 2405.08448 • Published • 19 -
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Paper • 2405.19332 • Published • 22 -
Offline Regularised Reinforcement Learning for Large Language Models Alignment
Paper • 2405.19107 • Published • 15 -
Show, Don't Tell: Aligning Language Models with Demonstrated Feedback
Paper • 2406.00888 • Published • 33
-
AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets
Paper • 2404.05623 • Published • 3 -
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Paper • 2405.19332 • Published • 22 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7 -
Deep Bayesian Active Learning for Preference Modeling in Large Language Models
Paper • 2406.10023 • Published • 2