https://github.com/nju-websoft/mbe
공식 코드Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities
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/nju-websoft/mmrag
공식 코드https://github.com/nju-websoft/mstar
공식 코드Expanding the Scope: Inductive Knowledge Graph Reasoning with Multi-Starting Progressive Propagation
https://github.com/nju-websoft/mukg
공식 코드$μ\text{KG}$: A Library for Multi-source Knowledge Graph Embeddings and Applications
https://github.com/nju-websoft/mukge
공식 코드https://github.com/nju-websoft/tkgc
공식 코드Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data
https://github.com/nju-websoft/unify-ea-sf
공식 코드https://github.com/nk-ruiying/tcompounde
공식 코드Simple but Effective Compound Geometric Operations for Temporal Knowledge Graph Completion
https://github.com/nkai-decision-team/llm-pysc2
공식 코드LLM-PySC2: Starcraft II learning environment for Large Language Models
https://github.com/nkanak/brag-fake-news-campaigns
공식 코드https://github.com/nl2code/attentioncoder
공식 코드Improving Natural Language Capability of Code Large Language Model
https://github.com/nl4opt/nl4opt-competition
공식 코드NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions
https://github.com/nle-ml/mmkb
공식 코드Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
https://github.com/nlp-bin/silc-efsa
공식 코드SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysis
https://github.com/nlp-tlp/cleangraph
공식 코드CleanGraph: Human-in-the-loop Knowledge Graph Refinement and Completion
https://github.com/nlp-uoregon/ullme
공식 코드ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning
https://github.com/nlp-waseda/comet-atomic-ja
공식 코드PHALM: Building a Knowledge Graph from Scratch by Prompting Humans and a Language Model
https://github.com/nlp2ct/hil-mt
공식 코드Human-in-the-loop Machine Translation with Large Language Model
https://github.com/nlpnorth/snakmodel
공식 코드SnakModel: Lessons Learned from Training an Open Danish Large Language Model
https://github.com/nmerkle/sw_journal
공식 코드https://github.com/nnnoidea/stateful-KGQA
공식 코드https://github.com/nolanoorg/spectrasuite
공식 코드Spectra: Surprising Effectiveness of Pretraining Ternary Language Models at Scale
https://github.com/nomic-ai/contrastors
공식 코드https://github.com/nomizy/think_net_prompt
공식 코드https://github.com/nomothings/charge
공식 코드Benchmarking Multimodal RAG through a Chart-based Document Question-Answering Generation Framework
https://github.com/norskregnesentral/conv_feedback
공식 코드Conversational Feedback in Scripted versus Spontaneous Dialogues: A Comparative Analysis
https://github.com/northsky0307/dppa-pruning-method-for-large-language-model-to-model-merging
공식 코드DPPA: Pruning Method for Large Language Model to Model Merging
https://github.com/novasearch-team/rag-retrieval
공식 코드Benchmarking the Myopic Trap: Positional Bias in Information Retrieval
https://github.com/novasky-ai/skythought
공식 코드LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
https://github.com/nslab-cuk/connector
공식 코드Connector 0.5: A unified framework for graph representation learning
https://github.com/ntuddsnlab/srgcl
공식 코드https://github.com/ntunlp/kmlm
공식 코드Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples
https://github.com/ntunlp/opensource-llms-better-than-openai
공식 코드ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
https://github.com/ntwalker/graphwoz
공식 코드GraphWOZ: Dialogue Management with Conversational Knowledge Graphs
https://github.com/nu-c3lab/satyrn
공식 코드https://github.com/nu-dialogue/jmultiwoz
공식 코드JMultiWOZ: A Large-Scale Japanese Multi-Domain Task-Oriented Dialogue Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.