https://github.com/mlii0117/dcl
공식 코드Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation
Papers with Code 아카이브
Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mllm-tool/mllm-tool
공식 코드MLLM-Tool: A Multimodal Large Language Model For Tool Agent Learning
https://github.com/mllmkcbench/mllmkc
공식 코드Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models
https://github.com/mlplyler/ICDA
공식 코드https://github.com/mlvlab/RALF
공식 코드https://github.com/mlvlab/llamo
공식 코드https://github.com/mmorris44/gnn-sound-rule-extraction
공식 코드Relational Graph Convolutional Networks Do Not Learn Sound Rules
https://github.com/mmurrad/tweet-data-classification
공식 코드Multi-Lingual Cyber Threat Detection in Tweets/X Using ML, DL, and LLM: A Comparative Analysis
https://github.com/mnoukhov/async_rlhf
공식 코드Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
https://github.com/mobs-fbk/llm_interaction_simulator
공식 코드https://github.com/modeeric/orbit-llama
공식 코드https://github.com/modelscope/mcpbench
공식 코드https://github.com/modeltc/llmc
공식 코드LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
https://github.com/modultechnology/affective-models-corpora
공식 코드Automatic Expansion of Domain-Specific Affective Models for Web Intelligence Applications
https://github.com/mohanraj-nlp/chatgpt-malaysian-english
공식 코드https://github.com/mohbattharani/kerl
공식 코드KERL: Knowledge-Enhanced Personalized Recipe Recommendation using Large Language Models
https://github.com/moment-timeseries-foundation-model/timeseriesgym
공식 코드TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
https://github.com/monarch-initiative/dragon-ai-results
공식 코드Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
https://github.com/monarch-initiative/gpt-ontology-completion-analysis
공식 코드Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
https://github.com/moonshotai/kimina-prover-preview
공식 코드Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement Learning
https://github.com/moonwalker1997/vsannkgalignment
공식 코드Aligning Knowledge Graphs Provided by Humans and Generated from Neural Networks in Specific Tasks
https://github.com/moreno98/gradbias
공식 코드GradBias: Unveiling Word Influence on Bias in Text-to-Image Generative Models
https://github.com/morganf33/gnr
공식 코드https://github.com/moritzblum/literalevaluation
공식 코드Numerical Literals in Link Prediction: A Critical Examination of Models and Datasets
https://github.com/mosesananta/qless
공식 코드QLESS: A Quantized Approach for Data Valuation and Selection in Large Language Model Fine-Tuning
https://github.com/mozerwang/loong
공식 코드Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA
https://github.com/mpi-lab/bc-hoi
공식 코드https://github.com/mpietrasik/hb
공식 코드https://github.com/mpietrasik/smich
공식 코드https://github.com/mramg-bench/mramg
공식 코드https://github.com/mrgiovanni/radgpt
공식 코드https://github.com/mrzilinxiao/autover
공식 코드https://github.com/msorkhpar/wiki-entity-summarization
공식 코드https://github.com/mstubbemann/Orometric-Methods-in-Bounded-Metric-Data
공식 코드https://github.com/mstubbemann/lg4av
공식 코드LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
https://github.com/mtkresearch/rad-bench
공식 코드RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.