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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 42 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2501.12895
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 13 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 54 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 47
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 106 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 43 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 29 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 19
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 257 -
Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 53 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10 -
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 23
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PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment
Paper • 2410.13785 • Published • 19 -
Aligning Large Language Models via Self-Steering Optimization
Paper • 2410.17131 • Published • 23 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 50 -
SemiEvol: Semi-supervised Fine-tuning for LLM Adaptation
Paper • 2410.14745 • Published • 47
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 42 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 56
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Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 66 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 45 -
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Paper • 2404.05892 • Published • 33 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 140
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Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 90 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 18 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 26
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 609 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 97 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 104 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 43