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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 67 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 126 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85
Collections
Discover the best community collections!
Collections including paper arxiv:2406.04770
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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 • 26 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 12 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 45 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 28
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 80 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 143 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 10 -
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
Paper • 2305.01210 • Published • 4 -
AGIBench: A Multi-granularity, Multimodal, Human-referenced, Auto-scoring Benchmark for Large Language Models
Paper • 2309.06495 • Published • 1 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35