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Large Language Model
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tu2021/rl-sallm-f
공식 코드https://github.com/tubehao/sinkt
공식 코드SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model
https://github.com/tuda-hwai/basis_sharing
공식 코드Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression
https://github.com/tuftsvalt/kgsinpractice
공식 코드https://github.com/tupyp7180/cft-rag-2025
공식 코드CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Filter
https://github.com/twilight92z/quantize-watermark
공식 코드https://github.com/txb-nju/exea
공식 코드Generating Explanations to Understand and Repair Embedding-based Entity Alignment
https://github.com/txh-mercury/vast
공식 코드VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset
https://github.com/txsun1997/CoLAKE
공식 코드https://github.com/tychenn/aqua
공식 코드Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment
https://github.com/tyler-griggs/melange-release
공식 코드Mélange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity
https://github.com/tylerachang/llm-behavior-survey
공식 코드https://github.com/tymadara/ils-csl
공식 코드Causal Structure Learning Supervised by Large Language Model
https://github.com/ubiquitouslearning/slm_survey
공식 코드https://github.com/uc-cdis/label-boosted-RAG-for-RRG
공식 코드LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generation
https://github.com/ucasyjz/VIP
공식 코드VIP: Versatile Image Outpainting Empowered by Multimodal Large Language Model
https://github.com/uchi-jcl/cachegen
공식 코드CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Serving
https://github.com/ucla-seal/provenanceinspector
공식 코드Human-in-the-Loop Synthetic Text Data Inspection with Provenance Tracking
https://github.com/uclanlp/diverse-factual
공식 코드https://github.com/uclnlp/cqd
공식 코드https://github.com/ucscirkm/sim-rag
공식 코드Knowing You Don't Know: Learning When to Continue Search in Multi-round RAG through Self-Practicing
https://github.com/ucsd-atp/propl
공식 코드https://github.com/ucsd-language-and-cognition-lab/nlm-fb
공식 코드https://github.com/uf-hobi-informatics-lab/gatortrongpt
공식 코드A Study of Generative Large Language Model for Medical Research and Healthcare
https://github.com/uiuc-conversational-ai-lab/accountable-dst
공식 코드https://github.com/uiuc-kang-lab/adaptiveattackagent
공식 코드Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents
https://github.com/uiuc-kang-lab/cve-bench
공식 코드CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities
https://github.com/uiuc-kang-lab/elt-bench
공식 코드ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines
https://github.com/uiuc-kang-lab/injecagent
공식 코드InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents
https://github.com/ukp-square/square-core
공식 코드UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA
https://github.com/ukplab/arxiv2024-attribute-or-abstain
공식 코드Attribute or Abstain: Large Language Models as Long Document Assistants
https://github.com/ukplab/arxiv2024-divergent-cot
공식 코드https://github.com/ukplab/arxiv2025-misleading-visualizations
공식 코드Protecting multimodal large language models against misleading visualizations
https://github.com/ukplab/iclr2025-psa
공식 코드Differentially Private Steering for Large Language Model Alignment
https://github.com/ukplab/peerqa
공식 코드PeerQA: A Scientific Question Answering Dataset from Peer Reviews
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.