https://github.com/yifanxu74/libra
공식 코드Libra: Building Decoupled Vision System on Large Language Models
Papers with Code 아카이브
Language Modeling
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yifanycc/sharpzo
공식 코드SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes
https://github.com/yifanzhang-pro/automathtext
공식 코드Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts
https://github.com/yifanzhang-pro/matrix-llm
공식 코드https://github.com/yifanzhang-pro/matrix-ssl
공식 코드https://github.com/yifding/hetseq
공식 코드HetSeq: Distributed GPU Training on Heterogeneous Infrastructure
https://github.com/yifeizhou02/archer
공식 코드ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
https://github.com/yigu1008/diffusion-rpo
공식 코드Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization
https://github.com/yihongdong/fan
공식 코드https://github.com/yihongdong/fanformer
공식 코드FANformer: Improving Large Language Models Through Effective Periodicity Modeling
https://github.com/yihwu/dipmark
공식 코드A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models
https://github.com/yikangshen/Ordered-Neurons
공식 코드Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
https://github.com/yikangshen/moa
공식 코드Mixture of Attention Heads: Selecting Attention Heads Per Token
https://github.com/yimjinkyu1/date2024_pipette
공식 코드Pipette: Automatic Fine-grained Large Language Model Training Configurator for Real-World Clusters
https://github.com/yinaoxiong/gaslt
공식 코드https://github.com/yinghao-li/gno-ie
공식 코드https://github.com/yinjunbo/cfpgen
공식 코드CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
https://github.com/yinyueqin/denserewardrlhf-ppo
공식 코드Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
https://github.com/yinyueqin/sapo
공식 코드Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment
https://github.com/yinzhangyue/eot
공식 코드Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communication
https://github.com/yiqingxyq/codebenchgen
공식 코드CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
https://github.com/yiren-jian/embedhalluc
공식 코드https://github.com/yiren-jian/lm-supcon
공식 코드Contrastive Learning for Prompt-Based Few-Shot Language Learners
https://github.com/yisuanwang/soulstyler
공식 코드Soulstyler: Using Large Language Model to Guide Image Style Transfer for Target Object
https://github.com/yitu-opensource/T2T-ViT
공식 코드Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
https://github.com/yixing-li/continuous-speech-tokenizer
공식 코드https://github.com/yiyiyizhao/nig4vi
공식 코드https://github.com/yjch00/plural
공식 코드https://github.com/yklochkov-bytedance/mt-unlearn
공식 코드https://github.com/ykumards/eclip
공식 코드Improving Medical Multi-modal Contrastive Learning with Expert Annotations
https://github.com/ykzhang0126/semanticcap
공식 코드SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language Model
https://github.com/yliu-cs/pite
공식 코드PiTe: Pixel-Temporal Alignment for Large Video-Language Model
https://github.com/ym-xiu/viddar-dataset
공식 코드ViDDAR: Vision Language Model-Based Task-Detrimental Content Detection for Augmented Reality
https://github.com/ym689/rec_icl
공식 코드Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning
https://github.com/ymcui/MacBERT
공식 코드Revisiting Pre-Trained Models for Chinese Natural Language Processing
https://github.com/ymcui/chinese-mixtral
공식 코드Rethinking LLM Language Adaptation: A Case Study on Chinese Mixtral
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.