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Requirements traceability is an essential step in ensuring the quality of software during the early stages of its development life cycle. Requirements tracing usually consists of document parsing, candidate link generation and evaluation…

软件工程 · 计算机科学 2015-06-30 Najla Al-Saati , Raghda Abdul-Jaleel

In the international software engineering research community, the premier conference (ICSE) features since a decade a special track on the role of SE In Society (or SEIS track). In this work, we want to use the articles published in this…

软件工程 · 计算机科学 2025-05-26 Iffat Fatima , Patricia Lago

This paper describes Toronto Metropolitan University's participation in the TREC Clinical Trials Track for 2023. As part of the tasks, we utilize advanced natural language processing techniques and neural language models in our experiments…

计算与语言 · 计算机科学 2024-03-21 Aritra Kumar Lahiri , Emrul Hasan , Qinmin Vivian Hu , Cherie Ding

Making the relevance judgments for a TREC-style test collection can be complex and expensive. A typical TREC track usually involves a team of six contractors working for 2-4 weeks. Those contractors need to be trained and monitored.…

信息检索 · 计算机科学 2025-03-27 Ian Soboroff

This paper summarizes the outcomes from the ISCSLP 2022 Intelligent Cockpit Speech Recognition Challenge (ICSRC). We first address the necessity of the challenge and then introduce the associated dataset collected from a new-energy vehicle…

声音 · 计算机科学 2022-11-04 Ao Zhang , Fan Yu , Kaixun Huang , Lei Xie , Longbiao Wang , Eng Siong Chng , Hui Bu , Binbin Zhang , Wei Chen , Xin Xu

The task of session search focuses on using interaction data to improve relevance for the user's next query at the session level. In this paper, we formulate session search as a personalization task under the framework of learning to rank.…

信息检索 · 计算机科学 2020-09-18 Saad Aloteibi , Stephen Clark

The Recherche Appliquee en Linguistique Informatique (RALI) team participated in the 2024 TREC Interactive Knowledge Assistance (iKAT) Track. In personalized conversational search, effectively capturing a user's complex search intent…

信息检索 · 计算机科学 2024-12-12 Yuchen Hui , Fengran Mo , Milan Mao , Jian-Yun Nie

This paper describes our participation in the TREC 2023 Deep Learning Track. We submitted runs that apply generative relevance feedback from a large language model in both a zero-shot and pseudo-relevance feedback setting over two sparse…

信息检索 · 计算机科学 2024-05-03 Andrew Parry , Thomas Jaenich , Sean MacAvaney , Iadh Ounis

Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinformation track. This paper presents our submissions to this…

信息检索 · 计算机科学 2021-12-14 Ipek Baris Schlicht , Angel Felipe Magnossão de Paula , Paolo Rosso

Fact tracing seeks to identify specific training examples that serve as the knowledge source for a given query. Existing approaches to fact tracing rely on assessing the similarity between each training sample and the query along a certain…

计算与语言 · 计算机科学 2024-04-24 Si Chen , Feiyang Kang , Ning Yu , Ruoxi Jia

Retrieval-augmented generation (RAG) offers an effective approach for addressing question answering (QA) tasks. However, the imperfections of the retrievers in RAG models often result in the retrieval of irrelevant information, which could…

计算与语言 · 计算机科学 2024-06-18 Jinyuan Fang , Zaiqiao Meng , Craig Macdonald

The ACM Lifelog Search Challenge (LSC) is a venue that welcomes and compares systems that support the exploration of lifelog data, and in particular the retrieval of specific information, through an interactive competition format. This…

In recent years, the task of mining important information from social media posts during crises has become a focus of research for the purposes of assisting emergency response (ES). The TREC Incident Streams (IS) track is a research…

计算与语言 · 计算机科学 2021-12-08 Congcong Wang , David Lillis

In this work we focus on multi-turn passage retrieval as a crucial component of conversational search. One of the key challenges in multi-turn passage retrieval comes from the fact that the current turn query is often underspecified due to…

信息检索 · 计算机科学 2020-05-26 Nikos Voskarides , Dan Li , Pengjie Ren , Evangelos Kanoulas , Maarten de Rijke

Pre-trained language models have been widely exploited to learn dense representations of documents and queries for information retrieval. While previous efforts have primarily focused on improving effectiveness and user satisfaction,…

信息检索 · 计算机科学 2025-05-01 Cristina Ioana Muntean , Franco Maria Nardini , Raffaele Perego , Guido Rocchietti , Cosimo Rulli

Universal Multimodal Retrieval requires unified embedding models capable of interpreting diverse user intents, ranging from simple keywords to complex compositional instructions. While Multimodal Large Language Models (MLLMs) possess strong…

计算机视觉与模式识别 · 计算机科学 2026-03-05 Xiangzhao Hao , Shijie Wang , Tianyu Yang , Tianyue Wang , Haiyun Guo , Jinqiao Wang

The present paper introduces a group activity involving writing summaries of conference proceedings by volunteer participants. The rapid increase in scientific papers is a heavy burden for researchers, especially non-native speakers, who…

计算机视觉与模式识别 · 计算机科学 2022-03-18 Shintaro Yamamoto , Hirokatsu Kataoka , Ryota Suzuki , Seitaro Shinagawa , Shigeo Morishima

Background. Coping with the rapid growing complexity in contemporary software architecture, tracing has become an increasingly critical practice and been adopted widely by software engineers. By adopting tracing tools, practitioners are…

软件工程 · 计算机科学 2023-06-26 Andrea Janes , Xiaozhou Li , Valentina Lenarduzzi

The CL-SciSumm Shared Task is the first medium-scale shared task on scientific document summarization in the computational linguistics~(CL) domain. In 2019, it comprised three tasks: (1A) identifying relationships between citing documents…

计算与语言 · 计算机科学 2019-07-24 Muthu Kumar Chandrasekaran , Michihiro Yasunaga , Dragomir Radev , Dayne Freitag , Min-Yen Kan

Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotated datasets. The purpose of the Learning from Imperfect Data…