https://bitbucket.org/TomKenter/attentive-memory-networks-code
공식 코드Attentive Memory Networks: Efficient Machine Reading for Conversational Search
Papers with Code 아카이브
Conversational Search
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AhmedHussKhalifa/Dense_Passage_Retrieval_in_Conversational_Search
공식 코드https://github.com/BeastyZ/ConvSearch-R1
공식 코드https://github.com/Guzpenha/transformer_rankers
공식 코드https://github.com/PengjieRen/CaSE-1.0
공식 코드Conversations with Search Engines: SERP-based Conversational Response Generation
https://github.com/SimonLupart/disco-conv-splade
공식 코드DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Search
https://github.com/ZahraAbbasiantaeb/LLMs-for-relevance-judgment-assessment
공식 코드Improving the Reusability of Conversational Search Test Collections
https://github.com/alexfrummet/cookversationalsearch
공식 코드https://github.com/ariya12138/convinv
공식 코드Interpreting Conversational Dense Retrieval by Rewriting-Enhanced Inversion of Session Embedding
https://github.com/castorini/duobert
공식 코드An Optimal Algorithm for Finding Champions in Tournament Graphs
https://github.com/chuanmeng/qpp-genre
공식 코드Can We Use Large Language Models to Fill Relevance Judgment Holes?
https://github.com/chuanmeng/qpp4cs
공식 코드Query Performance Prediction: From Ad-hoc to Conversational Search
https://github.com/chuzhumin98/convsearch-dataset
공식 코드Towards Better Understanding of User Satisfaction in Open-Domain Conversational Search
https://github.com/cnclabs/codes.cs.sampling
공식 코드Improving Conversational Passage Re-ranking with View Ensemble
https://github.com/dayuyang1999/zeqr
공식 코드ZeQR: Zero-shot Query Reformulation for Conversational Search
https://github.com/fengranMark/QRACDR
공식 코드Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search
https://github.com/fengranmark/chiq
공식 코드CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search
https://github.com/fengranmark/convgqr
공식 코드ConvGQR: Generative Query Reformulation for Conversational Search
https://github.com/fengranmark/convrelexpand
공식 코드Learning to Relate to Previous Turns in Conversational Search
https://github.com/fengranmark/convsdg
공식 코드https://github.com/fengranmark/haconvdr
공식 코드https://github.com/haon-chen/convaug
공식 코드Generalizing Conversational Dense Retrieval via LLM-Cognition Data Augmentation
https://github.com/hpclab/toploc_conv_search
공식 코드Efficient Conversational Search via Topical Locality in Dense Retrieval
https://github.com/i2lab/cikm21-conversational-search-strategies
공식 코드Analysing Mixed Initiatives and Search Strategies during Conversational Search
https://github.com/iai-group/cast-snippets
공식 코드https://github.com/iai-group/sigir2020-tablesum
공식 코드Summarizing and Exploring Tabular Data in Conversational Search
https://github.com/iai-group/sigir2024-transparentCIS
공식 코드Explainability for Transparent Conversational Information-Seeking
https://github.com/informagi/laps
공식 코드https://github.com/init0xyz/AdaCQR
공식 코드https://github.com/irlabamsterdam/cone-rag
공식 코드Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets
https://github.com/irlabamsterdam/iKAT
공식 코드TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistants
https://github.com/isekulic/chiir24-answer-rewriting
공식 코드Towards Self-Contained Answers: Entity-Based Answer Rewriting in Conversational Search
https://github.com/isekulic/mimics-EL-benchmark
공식 코드https://github.com/isekulic/usi
공식 코드Evaluating Mixed-initiative Conversational Search Systems via User Simulation
https://github.com/kixlab/searchgpt-classifier
공식 코드Using LLMs to Investigate Correlations of Conversational Follow-up Queries with User Satisfaction
https://github.com/kyriemao/chatretriever
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.