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/agentica-project/verl-pipeline

HybridFlow: A Flexible and Efficient RLHF Framework

https://github.com/agiresearch/litecua

LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem

https://github.com/ai4co/llm-as-hh

Algorithm Evolution Using Large Language Model

https://github.com/ai4co/reevo

Algorithm Evolution Using Large Language Model

https://github.com/aioz-ai/MICCAI21_MMQ

PathVQA: 30000+ Questions for Medical Visual Question Answering

https://github.com/aistairc/probing_sfqa

Pretrained Transformers for Simple Question Answering over Knowledge Graphs

https://github.com/alextakele/python-random-quote

RAGAS: Automated Evaluation of Retrieval Augmented Generation

https://github.com/ali7naseh/RAG_MIA

Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation

https://github.com/alibaba-nlp/webagent

WebWalker: Benchmarking LLMs in Web Traversal

https://github.com/alibaba/rtp-llm

Large Language Model based Long-tail Query Rewriting in Taobao Search

https://github.com/alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE

Open Graph Benchmark: Datasets for Machine Learning on Graphs

https://github.com/alisadeghian/DRUM

DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs

https://github.com/allenai/commonsense-kg-completion

Commonsense Knowledge Base Completion with Structural and Semantic Context

https://github.com/allenai/kb

TuckER: Tensor Factorization for Knowledge Graph Completion

https://github.com/alpha-innovator/chartvlm

StructChart: On the Schema, Metric, and Augmentation for Visual Chart Understanding

https://github.com/amazon-science/SDFeedback

Teaching Large Language Models to Self-Debug

https://github.com/amazon-science/self_debug

Teaching Large Language Models to Self-Debug

https://github.com/anandaswarup/phrase_break_prediction

Phrase break prediction with bidirectional encoder representations in Japanese text-to-speech synthesis

https://github.com/andypinxinliu/GestureLSM

Retrieving Semantics from the Deep: an RAG Solution for Gesture Synthesis

https://github.com/anilakash/indkgc

Modeling Relational Data with Graph Convolutional Networks

https://github.com/anonymous-dense-submission/DensE

DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic Hierarchy

https://github.com/anonymous20221001/sieg_ogb

Open Graph Benchmark: Datasets for Machine Learning on Graphs

https://github.com/ant-research/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE

Open Graph Benchmark: Datasets for Machine Learning on Graphs

https://github.com/ant-research/structuredlm_rtdt

Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text Representation

https://github.com/apoorvumang/prompt-lookup-decoding

Accelerating Large Language Model Decoding with Speculative Sampling

https://github.com/appsec2008/acnbp

Agent Name Service (ANS): A Universal Directory for Secure AI Agent Discovery and Interoperability

https://github.com/artessay/ragraph

TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems

https://github.com/aryaze/testpilot

An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation

https://github.com/asannasi/txt_adv_nlp

Text-based Adventures of the Golovin AI Agent

https://github.com/asarigun/DrugGEN

A Generalization of Transformer Networks to Graphs

https://github.com/assafelovic/gpt-researcher

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

https://github.com/atcbosselut/comet-commonsense

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

https://github.com/aubrey-ao/humanbehavioranimation

Semantic Gesticulator: Semantics-Aware Co-Speech Gesture Synthesis

https://github.com/autoliuweijie/K-BERT

K-BERT: Enabling Language Representation with Knowledge Graph

https://github.com/automl-research/red-gnn

Inductive Relation Prediction by Subgraph Reasoning

https://github.com/awslabs/dgl-ke

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.