https://github.com/towhidabsar/communityneeds
공식 코드Community Needs and Assets: A Computational Analysis of Community Conversations
Papers with Code 아카이브
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/tpekarekrosin/uhh_ub_ageawarehri
공식 코드A Framework for Adapting Human-Robot Interaction to Diverse User Groups
https://github.com/tqfang/complex-commonsense-reasoning
공식 코드Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs
https://github.com/trae1oung/dyprag
공식 코드Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement
https://github.com/traffic-alpha/illm-tsc
공식 코드https://github.com/traffic-alpha/llm-assisted-light
공식 코드https://github.com/tranhungnghiep/AnalyzeKGE
공식 코드Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective
https://github.com/tranhungnghiep/KG20C
공식 코드Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space
https://github.com/tranhungnghiep/meim-kge
공식 코드https://github.com/travis-xu/TR-Feedback
공식 코드Enhancing Tool Retrieval with Iterative Feedback from Large Language Models
https://github.com/tree-jhk/reckg
공식 코드https://github.com/treeai-lab/awesome-kv-cache-management
공식 코드A Survey on Large Language Model Acceleration based on KV Cache Management
https://github.com/trishullab/LibraryAugmentedSymbolicRegression.jl
공식 코드https://github.com/trishullab/copra
공식 코드https://github.com/trustedllm/llmdet
공식 코드LLMDet: A Third Party Large Language Models Generated Text Detection Tool
https://github.com/trustworthy-ml-lab/cb-llms
공식 코드https://github.com/truthai-lab/soradetector
공식 코드Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models
https://github.com/tsafavi/codex
공식 코드https://github.com/tsinghua-dhy/edc-2-rag
공식 코드Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation
https://github.com/tsinghua-fib-lab/acl24-econagent
공식 코드EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities
https://github.com/tsinghua-fib-lab/agentmove
공식 코드AgentMove: Predicting Human Mobility Anywhere Using Large Language Model based Agentic Framework
https://github.com/tsinghua-fib-lab/agentsocietychallenge
공식 코드AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms
https://github.com/tsinghua-fib-lab/agentstealth
공식 코드AgentStealth: Reinforcing Large Language Model for Anonymizing User-generated Text
https://github.com/tsinghua-fib-lab/citybench
공식 코드CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
https://github.com/tsinghua-fib-lab/limp
공식 코드LIMP: Large Language Model Enhanced Intent-aware Mobility Prediction
https://github.com/tsinghua-fib-lab/llm-agent-for-recommendation-and-search
공식 코드https://github.com/tsinghua-fib-lab/trajagent
공식 코드TrajAgent: An Agent Framework for Unified Trajectory Modelling
https://github.com/tsinghuac3i/crash
공식 코드CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model
https://github.com/tsukushiai/self-organized-agent
공식 코드https://github.com/tsynbio/autope
공식 코드https://github.com/tsynbio/proteinlmdataset
공식 코드A Fine-tuning Dataset and Benchmark for Large Language Models for Protein Understanding
https://github.com/ttrouill/complex
공식 코드https://github.com/ttrouill/induction_experiments
공식 코드On Inductive Abilities of Latent Factor Models for Relational Learning
https://github.com/ttttttris/flat-llm
공식 코드FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression
https://github.com/ttuhamg/texttoucher
공식 코드https://github.com/tu2021/rl-sallm-f
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.