Conversational Search

44 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

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.

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.

Conversations with Search Engines: SERP-based Conversational Response Generation

PengjieRen/CaSE-1.0 29 Apr 2020

In this paper, we address the problem of answering complex information needs by conversing conversations with search engines, in the sense that users can express their queries in natural language, and directly receivethe information they need from a short system response in a conversational manner.

Open-Retrieval Conversational Question Answering

prdwb/orconvqa-release 22 May 2020

We build an end-to-end system for ORConvQA, featuring a retriever, a reranker, and a reader that are all based on Transformers.

Summarizing and Exploring Tabular Data in Conversational Search

iai-group/sigir2020-tablesum 23 May 2020

We propose to generate natural language summaries as answers to describe the complex information contained in a table.