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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 24 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 36 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2403.05530
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 10 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 48 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 44
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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 • 78 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Paper • 2408.15545 • Published • 31 -
Controllable Text Generation for Large Language Models: A Survey
Paper • 2408.12599 • Published • 59 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 38 -
Automated Design of Agentic Systems
Paper • 2408.08435 • Published • 37
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OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 78 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 59 -
StarCoder: may the source be with you!
Paper • 2305.06161 • Published • 29 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 56
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Attention Is All You Need
Paper • 1706.03762 • Published • 41 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 14 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 14 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 11
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 54 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 24 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 65 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 55