Results for “language-learning”
28 skillsMore results
chrismccoy Language Tutor
Language Tutor
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jiachen-t-wang Glip Grounded Language Image Pre Training Arxiv 2112 03857v2
GLIP: Grounded Language-Image Pre-training
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jiachen-t-wang Lora Low Rank Adaptation Of Large Language Models Arxiv 2106
LoRA: Low-Rank Adaptation of Large Language Models
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jarbitechture Learn
Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.
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jiachen-t-wang Sigmoid Loss For Language Image Pre Training Arxiv 2303 1534
Sigmoid Loss for Language Image Pre-Training
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jiachen-t-wang Deduplicating Training Data Makes Language Models Better Arx
Deduplicating Training Data Makes Language Models Better
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jiachen-t-wang Scaling Instruction Finetuned Language Models Arxiv 2210 114
Scaling Instruction-Finetuned Language Models
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jiachen-t-wang Cogvlm Visual Expert For Pretrained Language Models Arxiv 23
CogVLM: Visual Expert for Pretrained Language Models
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qcmuu Blip 2 Vision Language
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
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jiachen-t-wang Laclip Improving Clip Training With Language Rewrites Arxiv
LaCLIP: Improving CLIP Training with Language Rewrites
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orchestra-research Blip 2 Vision Language
Generate image captions, answer visual questions, and perform image-text retrieval using BLIP-2's Q-Former architecture with frozen vision encoders and LLMs.
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tianhao909 Blip 2 Vision Language
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
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jiachen-t-wang Scaling Data Constrained Language Models Arxiv 2305 16264v3
Scaling Data-Constrained Language Models
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jiachen-t-wang Dreamlip Language Image Pre Training With Long Captions Arxi
DreamLIP: Language-Image Pre-training with Long Captions
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jiachen-t-wang Hard Negative Mixing For Contrastive Learning Arxiv 2010 010
Hard Negative Mixing for Contrastive Learning
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jiachen-t-wang Training Compute Optimal Large Language Models Arxiv 2203 15
Training Compute-Optimal Large Language Models
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jiachen-t-wang Llava Next Improved Reasoning Ocr And World Knowledge Arxiv
LLaVA-NeXT: Improved Reasoning, OCR, and World Knowledge
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jiachen-t-wang Autoaugment Learning Augmentation Strategies From Data Arxiv
AutoAugment: Learning Augmentation Strategies from Data
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salacoste Learner
Extract a learned skill from the current conversation
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bouclem Deep Learning
PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production
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jiachen-t-wang Dclm Datacomp For Language Models Arxiv 2406 11794v3
DCLM: DataComp for Language Models
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arustydev Meta Convert Dev
Create language conversion skills for translating code from language A to language B. Use when building 'convert-X-Y' skills, designing type mappings between languages, establishing idiom translation patterns, or defining conversion methodologies. Provides foundational patterns that specific conversion skills extend.
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shenxingy Learn
Record, search, and prune per-project learnings in .claude/learnings.jsonl — typed, confidence-scored, searchable across sessions
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jiachen-t-wang Nlvr2 A Visual Reasoning Benchmark For Natural Language Arxi
NLVR2: A Visual Reasoning Benchmark for Natural Language
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lord1egypt Llava
Runs the open-source LLaVA vision-language model for image understanding, captioning, visual question answering, and multi-turn image conversations, including setup, inference, and training guidance.
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dracounion Project Based Learning
当需要快速掌握一门新技能或知识领域，且希望通过实践而非单纯理论学习时
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dracounion Learn By Teaching
当需要深化对某个主题的理解、检验知识掌握程度或克服“冒名顶替综合征”时
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