Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wilcoxeg/targeted-assessment-imaze
공식 코드A Targeted Assessment of Incremental Processing in Neural LanguageModels and Humans
https://github.com/wilkox/gptscreenr
공식 코드Automated title and abstract screening for scoping reviews using the GPT-4 Large Language Model
https://github.com/willemeng/VLScene
공식 코드VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion
https://github.com/willemsenbram/mention-detection-vgd
공식 코드Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models
https://github.com/willemsenbram/reference-resolution-via-text-generation
공식 코드Resolving References in Visually-Grounded Dialogue via Text Generation
https://github.com/willhawkins3/finetuningtoxicity
공식 코드https://github.com/williamliujl/Qilin-Med
공식 코드Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
https://github.com/williamliujl/qilin-med-vl
공식 코드Qilin-Med-VL: Towards Chinese Large Vision-Language Model for General Healthcare
https://github.com/williamzr/recipe2plan
공식 코드https://github.com/willxxy/ecg-byte
공식 코드ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling
https://github.com/willxxy/text-egm
공식 코드Interpretation of Intracardiac Electrograms Through Textual Representations
https://github.com/windvchen/diff-harmonization
공식 코드https://github.com/wishever/mmidr
공식 코드https://github.com/wisper12933/ga-rollback
공식 코드Generator-Assistant Stepwise Rollback Framework for Large Language Model Agent
https://github.com/wivizhang/earthgpt
공식 코드https://github.com/wivizhang/earthmarker
공식 코드EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote Sensing
https://github.com/wiwu2390/futuregpt2-public
공식 코드https://github.com/wj210/Self-Training-LLM
공식 코드Self-training Large Language Models through Knowledge Detection
https://github.com/wjn1996/kp-plm
공식 코드Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding
https://github.com/wjurayj/garden-path-gpt2
공식 코드https://github.com/wjxts/regularizedbn
공식 코드Understanding the Failure of Batch Normalization for Transformers in NLP
https://github.com/wlik/glrec
공식 코드Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations
https://github.com/wlin12/JNN
공식 코드Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation
https://github.com/wojciechowskiofficial/flex
공식 코드Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach
https://github.com/wojzaremba/lstm
공식 코드https://github.com/woojeongjin/fewvlm
공식 코드https://github.com/woooodyy/agentgym
공식 코드AgentGym: Evolving Large Language Model-based Agents across Diverse Environments
https://github.com/woooodyy/llm-agent-paper-list
공식 코드The Rise and Potential of Large Language Model Based Agents: A Survey
https://github.com/wordsgpt/llm_vocabulary_evaluation
공식 코드Establishing Vocabulary Tests as a Benchmark for Evaluating Large Language Models
https://github.com/work4cs/sensei
공식 코드https://github.com/worta/trojansteno
공식 코드TrojanStego: Your Language Model Can Secretly Be A Steganographic Privacy Leaking Agent
https://github.com/wqxleo/kcf-plm
공식 코드https://github.com/wtma/CharBERT
공식 코드https://github.com/wuhy68/chatedav1
공식 코드ChatEDA: A Large Language Model Powered Autonomous Agent for EDA
https://github.com/wujiangxu/slmrec
공식 코드SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.