Conversational Search

66 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Ranking Manipulation for Conversational Search Engines

spfrommer/ranking_manipulation_data_pipeline 5 Jun 2024

These conversational search engines operate by loading retrieved website text into the LLM context for summarization and interpretation.

V3CTRON | Data Retrieval & Access System For Flexible Semantic Search & Retrieval Of Proprietary Document Collections Using Natural Language Queries.

serp-ai/V3CTRON-vector-database-embedding-neural-search-retrieval-chatgpt-plugin Social Science Research Network (SSRN) 2023

V3CTRON is an open source vector database that allows users to upload text based documents & document collections, which are automatically embedded for super-accurate semantic search & retrieval using natural language queries.

Attentive History Selection for Conversational Question Answering

prdwb/attentive_history_selection 26 Aug 2019

First, we propose a positional history answer embedding method to encode conversation history with position information using BERT in a natural way.

Introducing MANtIS: a novel Multi-Domain Information Seeking Dialogues Dataset

Guzpenha/MANtIS 10 Dec 2019

Conversational search is an approach to information retrieval (IR), where users engage in a dialogue with an agent in order to satisfy their information needs.

Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search

kyriemao/llm4cs 12 Mar 2023

Precisely understanding users' contextual search intent has been an important challenge for conversational search.

Detecting Generated Native Ads in Conversational Search

webis-de/ads-in-generative-ir 7 Feb 2024

In this paper, we thus take a first step to investigate whether LLMs can also be used as a countermeasure, i. e., to block generated native ads.

Attentive Memory Networks: Efficient Machine Reading for Conversational Search

TomKenter/attentive-memory-networks-code 19 Dec 2017

We argue that the process of building a representation of the conversation can be framed as a machine reading task, where an automated system is presented with a number of statements about which it should answer questions.

User Intent Prediction in Information-seeking Conversations

prdwb/UserIntentPrediction 11 Jan 2019

Due to the limited communication bandwidth in conversational search, it is important for conversational assistants to accurately detect and predict user intent in information-seeking conversations.

BERT with History Answer Embedding for Conversational Question Answering

prdwb/bert_hae 14 May 2019

One of the major challenges to multi-turn conversational search is to model the conversation history to answer the current question.

TREC CAsT 2019: The Conversational Assistance Track Overview

daltonj/treccastweb 30 Mar 2020

A common theme through the runs is the use of BERT-based neural reranking methods.