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Language Modeling
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shumkashun/first
공식 코드FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillation
https://github.com/shumpei19/jet
공식 코드Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation
https://github.com/shuohangwang/Cross-Thought
공식 코드https://github.com/shuozhangxjtu/mixalign
공식 코드The Knowledge Alignment Problem: Bridging Human and External Knowledge for Large Language Models
https://github.com/shuyao95/Understanding-NAS
공식 코드Understanding Architectures Learnt by Cell-based Neural Architecture Search
https://github.com/si0wang/visvm
공식 코드Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension
https://github.com/sichunluo/rallrec_plus
공식 코드RALLRec+: Retrieval Augmented Large Language Model Recommendation with Reasoning
https://github.com/sichunluo/recranker
공식 코드RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation
https://github.com/sierkinhane/visorgpt
공식 코드https://github.com/sike-wang/low-bit-shampoo
공식 코드https://github.com/sileod/language-model-recommendation
공식 코드https://github.com/sileod/llm-theory-of-mind
공식 코드MindGames: Targeting Theory of Mind in Large Language Models with Dynamic Epistemic Modal Logic
https://github.com/silin159/seknow
공식 코드End-to-End Task-Oriented Dialog Modeling with Semi-Structured Knowledge Management
https://github.com/simbianai/taskgen
공식 코드TaskGen: A Task-Based, Memory-Infused Agentic Framework using StrictJSON
https://github.com/simengsun/iga-an-intent-guided-authoring-assistant
공식 코드https://github.com/simplescaling/s1
공식 코드https://github.com/singularity0104/equilibrium-planner
공식 코드Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
https://github.com/sintel-dev/sigllm
공식 코드Large language models can be zero-shot anomaly detectors for time series?
https://github.com/sisl/astprompter
공식 코드https://github.com/siyan-sylvia-li/icarus_final
공식 코드When can I Speak? Predicting initiation points for spoken dialogue agents
https://github.com/siyan-sylvia-li/papillon
공식 코드PAPILLON: Privacy Preservation from Internet-based and Local Language Model Ensembles
https://github.com/sjdai/llm-thematic-analysis
공식 코드LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis
https://github.com/sjj1017/citekit
공식 코드Citekit: A Modular Toolkit for Large Language Model Citation Generation
https://github.com/sjkrol/gpt3musicalexplanationsdata
공식 코드https://github.com/sjmeis/DPNONDP
공식 코드https://github.com/sjmielke/spell-once
공식 코드Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model
https://github.com/sjtu-ipads/powerinfer
공식 코드PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU
https://github.com/sjtu-lit/pem_composition
공식 코드Composing Parameter-Efficient Modules with Arithmetic Operations
https://github.com/sjtu-yc/idfree-personalized-learning
공식 코드Personalized Language Model Learning on Text Data Without User Identifiers
https://github.com/sjyyj/sjyyj
공식 코드RTSUM: Relation Triple-based Interpretable Summarization with Multi-level Salience Visualization
https://github.com/skangasl/continuous-lm-interpolation
공식 코드Continuous Language Model Interpolation for Dynamic and Controllable Text Generation
https://github.com/skgabriel/mh-eval
공식 코드Can AI Relate: Testing Large Language Model Response for Mental Health Support
https://github.com/skit-ai/slu-prosody
공식 코드Improving End-to-End SLU performance with Prosodic Attention and Distillation
https://github.com/skjack/vlffd
공식 코드Towards General Visual-Linguistic Face Forgery Detection(V2)
https://github.com/sky-fish23/eike
공식 코드Embedding Ontologies via Incorporating Extensional and Intensional Knowledge
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.