Search Results for author:
Found 28 papers, 13 papers with code
Robustness Evaluation of Entity Disambiguation Using Prior Probes: the Case of Entity Overshadowing
We evaluate and report the performance of popular EL systems on the ShadowLink benchmark.
Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study
Additionally, we select two scene-centric datasets, and three object-centric datasets, and determine the relative performance of the selected models on these datasets.
Focusing on Context is NICE: Improving Overshadowed Entity Disambiguation
Entity disambiguation (ED) is the task of mapping an ambiguous entity mention to the corresponding entry in a structured knowledge base.
On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answering
Finally, we create a new dataset with questions voiced by human users and use their transcriptions to show that the retrieval performance can further degrade when dealing with natural ASR noise instead of synthetic ASR noise.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey
Dense retrieval (DR) approaches based on powerful pre-trained language models (PLMs) achieved significant advances and have become a key component for modern open-domain question-answering systems.
A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration
The cross-entropy objective has proved to be an all-purpose training objective for autoregressive language models (LMs).
SCAI-QReCC Shared Task on Conversational Question Answering
Search-Oriented Conversational AI (SCAI) is an established venue that regularly puts a spotlight upon the recent work advancing the field of conversational search.
Extending CLIP for Category-to-image Retrieval in E-commerce
One aspect of this data is a category tree that is being used in search and recommendation.
Tackling Query-Focused Summarization as A Knowledge-Intensive Task: A Pilot Study
In this dataset, answering the query requires document retrieval from a knowledge corpus.
Robustness Evaluation of Entity Disambiguation Using Prior Probes:the Case of Entity Overshadowing
We evaluate and report the performance of popular EL systems on the ShadowLink benchmark.
VerbCL: A Dataset of Verbatim Quotes for Highlight Extraction in Case Law
Citing legal opinions is a key part of legal argumentation, an expert task that requires retrieval, extraction and summarization of information from court decisions.
Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering
In simple open-domain question answering (QA), dense retrieval has become one of the standard approaches for retrieving the relevant passages to infer an answer.
Multi-hop Question Answering
Open-Domain Question Answering
+2
A Large-Scale Analysis of Mixed Initiative in Information-Seeking Dialogues for Conversational Search
These datasets were collected to inform different dialogue-based tasks including conversational search.
Leveraging Query Resolution and Reading Comprehension for Conversational Passage Retrieval
This paper describes the participation of UvA. ILPS group at the TREC CAsT 2020 track.
A Comparison of Question Rewriting Methods for Conversational Passage Retrieval
Conversational passage retrieval relies on question rewriting to modify the original question so that it no longer depends on the conversation history.
Conversational Browsing
How can we better understand the mechanisms behind multi-turn information seeking dialogues?
A Wrong Answer or a Wrong Question? An Intricate Relationship between Question Reformulation and Answer Selection in Conversational Question Answering
The dependency between an adequate question formulation and correct answer selection is a very intriguing but still underexplored area.
Open-Domain Question Answering Goes Conversational via Question Rewriting
We introduce a new dataset for Question Rewriting in Conversational Context (QReCC), which contains 14K conversations with 80K question-answer pairs.
An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues
The ability to engage in mixed-initiative interaction is one of the core requirements for a conversational search system.
Question Rewriting for Conversational Question Answering
Conversational question answering (QA) requires the ability to correctly interpret a question in the context of previous conversation turns.
Common Conversational Community Prototype: Scholarly Conversational Assistant
This paper discusses the potential for creating academic resources (tools, data, and evaluation approaches) to support research in conversational search, by focusing on realistic information needs and conversational interactions.
Knowledge-based Conversational Search
In the third research chapter, we propose a novel approach for complex question answering from a knowledge graph that surpasses the current state-of-the-art results in terms of both efficacy and efficiency.
Open Data Chatbot
Recently, chatbots received an increased attention from industry and diverse research communities as a dialogue-based interface providing advanced human-computer interactions.
Message Passing for Complex Question Answering over Knowledge Graphs
We propose a novel approach for complex KGQA that uses unsupervised message passing, which propagates confidence scores obtained by parsing an input question and matching terms in the knowledge graph to a set of possible answers.
QRFA: A Data-Driven Model of Information-Seeking Dialogues
Understanding the structure of interaction processes helps us to improve information-seeking dialogue systems.
Measuring Semantic Coherence of a Conversation
Conversational systems have become increasingly popular as a way for humans to interact with computers.
Conversational Exploratory Search via Interactive Storytelling
In this paper we investigate the affordances of interactive storytelling as a tool to enable exploratory search within the framework of a conversational interface.
Character-based Neural Embeddings for Tweet Clustering
In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks.
