https://github.com/um2ii/text2cohort
공식 코드Text2Cohort: Facilitating Intuitive Access to Biomedical Data with Natural Language Cohort Discovery
Papers with Code 아카이브
Large Language Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/uma-pi1/grash
공식 코드Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings
https://github.com/uma-pi1/kgt5-context
공식 코드Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction
https://github.com/uma-pi1/wikidata5m-si
공식 코드A Benchmark for Semi-Inductive Link Prediction in Knowledge Graphs
https://github.com/umanlp/spkatt-2023
공식 코드Speaker attribution in German parliamentary debates with QLoRA-adapted large language models
https://github.com/umass-ml4ed/prompt_distractor_generation_naacl
공식 코드https://github.com/umass-ml4ed/reticl
공식 코드RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning
https://github.com/umass-ml4ed/syllabusqa
공식 코드https://github.com/umass-ml4ed/test_case_generation
공식 코드https://github.com/umass-ml4ed/tiktoc
공식 코드Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks
https://github.com/umd-huang-lab/mementos
공식 코드https://github.com/unibwtas/collisionpro
공식 코드Collision Probability Distribution Estimation via Temporal Difference Learning
https://github.com/unicamp-dl/exaranker
공식 코드https://github.com/unified-language-model-alignment/src
공식 코드ULMA: Unified Language Model Alignment with Human Demonstration and Point-wise Preference
https://github.com/unimodal4reasoning/chartvlm
공식 코드StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
https://github.com/unimodal4reasoning/simchart9k
공식 코드StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding
https://github.com/upper9527/gerea
공식 코드GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question Answering
https://github.com/upstageai/evalverse
공식 코드Evalverse: Unified and Accessible Library for Large Language Model Evaluation
https://github.com/uq-neusoft-health-data-science/activeea
공식 코드https://github.com/uqbingliu/emea
공식 코드https://github.com/uqbingliu/stea
공식 코드https://github.com/urban-world/urbanworld
공식 코드https://github.com/urchade/enrico
공식 코드https://github.com/usail-hkust/CoLLMLight
공식 코드CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control
https://github.com/usail-hkust/urbankgent
공식 코드UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction
https://github.com/usail-hkust/uukg
공식 코드UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
https://github.com/usc-isi-i2/cskg
공식 코드https://github.com/usc-isi-i2/kgtk
공식 코드KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis
https://github.com/usc-isi-i2/kgtk-similarity
공식 코드User-friendly Comparison of Similarity Algorithms on Wikidata
https://github.com/ustcagi/crag-in-kdd-cup2024
공식 코드https://github.com/ustcagi/pruningrag
공식 코드Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
https://github.com/ustcagi/rag-x
공식 코드Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
https://github.com/uta-sprlab/phishlang
공식 코드PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
https://github.com/utnslab/halos
공식 코드https://github.com/uva-dsa/dkec
공식 코드DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction
https://github.com/vahe1994/spqr
공식 코드SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.