https://github.com/zjunlp/promptkg
공식 코드LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings
Papers with Code 아카이브
Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zjunlp/steer-target-atoms
공식 코드Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms
https://github.com/zjunlp/trice
공식 코드Making Language Models Better Tool Learners with Execution Feedback
https://github.com/zjwang21/syncs
공식 코드Investigating and Scaling up Code-Switching for Multilingual Language Model Pre-Training
https://github.com/zlinao/VGLM
공식 코드Exploring Versatile Generative Language Model Via Parameter-Efficient Transfer Learning
https://github.com/znlp/x-instruction
공식 코드https://github.com/zodiark-ch/emergence-of-llms
공식 코드https://github.com/zomss/co-prompt
공식 코드Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker
https://github.com/zonetrooper32/robot_semantics
공식 코드https://github.com/zorazrw/agent-workflow-memory
공식 코드https://github.com/zou-group/avatar
공식 코드AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
https://github.com/zouharvi/sentence-embd-fusion
공식 코드Fusing Sentence Embeddings Into LSTM-based Autoregressive Language Models
https://github.com/zr2021/2021_qq_aiac_tack1_1st
공식 코드Top1 Solution of QQ Browser 2021 Ai Algorithm Competition Track 1 : Multimodal Video Similarity
https://github.com/zsquaredz/adapt_vs_finetune
공식 코드To Adapt or to Fine-tune: A Case Study on Abstractive Summarization
https://github.com/zsquaredz/subpopulation_analysis
공식 코드Understanding Domain Learning in Language Models Through Subpopulation Analysis
https://github.com/zuela-ai/angofa
공식 코드ANGOFA: Leveraging OFA Embedding Initialization and Synthetic Data for Angolan Language Model
https://github.com/zurichnlp/recognizing-semantic-differences
공식 코드Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents
https://github.com/zurichnlp/swissbert
공식 코드https://github.com/zwanah/DataVisT5
공식 코드DataVisT5: A Pre-trained Language Model for Jointly Understanding Text and Data Visualization
https://github.com/zwq2018/multi-modal-self-instruct
공식 코드https://github.com/zwq803/mm-skin
공식 코드https://github.com/zxccade/shine
공식 코드SHINE: Saliency-aware HIerarchical NEgative Ranking for Compositional Temporal Grounding
https://github.com/zxzhao0/c2ser
공식 코드https://github.com/zygmuntz/hyperband
공식 코드https://github.com/zyloveslego/LLMCheck
공식 코드https://github.com/zyphra/blackmamba
공식 코드https://github.com/zyphra/zyda_processing
공식 코드https://github.com/zytx121/geoground
공식 코드GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding
https://github.com/zyzisastudyreallyhardguy/llm4sd
공식 코드Large Language Models for Scientific Synthesis, Inference and Explanation
https://github.com/zz1358m/mcts-ahd-master
공식 코드Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
https://github.com/zzbuzzard/guidediffuseq
공식 코드Understanding the Quality-Diversity Trade-off in Diffusion Language Models
https://github.com/zzeng13/pier
공식 코드Unified Representation for Non-compositional and Compositional Expressions
https://github.com/zzh-z/rochbert
공식 코드https://github.com/zzshou/RCAM
공식 코드https://gitlab.com/boshko.koloski/codename_fn_b
공식 코드Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles
https://gitlab.com/chen00217/bert_subsumption
공식 코드Contextual Semantic Embeddings for Ontology Subsumption Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.