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Internal Consistency and Self-Feedback in Large Language Models: A Survey
Paper • 2407.14507 • Published • 46 -
New Desiderata for Direct Preference Optimization
Paper • 2407.09072 • Published • 9 -
Self-Recognition in Language Models
Paper • 2407.06946 • Published • 24 -
MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
Paper • 2407.04842 • Published • 52
Collections
Discover the best community collections!
Collections including paper arxiv:2406.09760
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Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
sail/Llama-3-Base-8B-DICE-Iter1
Text Generation • Updated • 45 • 1 -
sail/Llama-3-Base-8B-DICE-Iter2
Text Generation • Updated • 43 • 2 -
sail/Zephyr-7B-DICE-Iter1
Text Generation • Updated • 69
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Instruction Pre-Training: Language Models are Supervised Multitask Learners
Paper • 2406.14491 • Published • 85 -
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 63 -
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Paper • 2405.20541 • Published • 20 -
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 42
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Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Paper • 2406.11931 • Published • 57 -
Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs
Paper • 2406.14544 • Published • 34 -
Instruction Pre-Training: Language Models are Supervised Multitask Learners
Paper • 2406.14491 • Published • 85
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Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 40
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WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
Self-Improving Robust Preference Optimization
Paper • 2406.01660 • Published • 18 -
Bootstrapping Language Models with DPO Implicit Rewards
Paper • 2406.09760 • Published • 38 -
BPO: Supercharging Online Preference Learning by Adhering to the Proximity of Behavior LLM
Paper • 2406.12168 • Published • 7
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Understanding the performance gap between online and offline alignment algorithms
Paper • 2405.08448 • Published • 14 -
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Paper • 2405.19332 • Published • 15 -
Offline Regularised Reinforcement Learning for Large Language Models Alignment
Paper • 2405.19107 • Published • 13 -
Show, Don't Tell: Aligning Language Models with Demonstrated Feedback
Paper • 2406.00888 • Published • 30
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Suppressing Pink Elephants with Direct Principle Feedback
Paper • 2402.07896 • Published • 9 -
Policy Improvement using Language Feedback Models
Paper • 2402.07876 • Published • 5 -
Direct Language Model Alignment from Online AI Feedback
Paper • 2402.04792 • Published • 29 -
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Paper • 2401.01335 • Published • 64
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18 -
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition
Paper • 2402.15220 • Published • 19 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6