Multi-document summarization via deep learning techniques: A survey

C Ma, WE Zhang, M Guo, H Wang, QZ Sheng - ACM Computing Surveys, 2022‏ - dl.acm.org
Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …

Exploring the limits of chatgpt for query or aspect-based text summarization

X Yang, Y Li, X Zhang, H Chen, W Cheng - arxiv preprint arxiv …, 2023‏ - arxiv.org
Text summarization has been a crucial problem in natural language processing (NLP) for
several decades. It aims to condense lengthy documents into shorter versions while …

QMSum: A new benchmark for query-based multi-domain meeting summarization

M Zhong, D Yin, T Yu, A Zaidi, M Mutuma, R Jha… - arxiv preprint arxiv …, 2021‏ - arxiv.org
Meetings are a key component of human collaboration. As increasing numbers of meetings
are recorded and transcribed, meeting summaries have become essential to remind those …

Pre-training methods in information retrieval

Y Fan, X **e, Y Cai, J Chen, X Ma, X Li… - … and Trends® in …, 2022‏ - nowpublishers.com
The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …

Chatgpt's one-year anniversary: are open-source large language models catching up?

H Chen, F Jiao, X Li, C Qin, M Ravaut, R Zhao… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of
AI, both in research and commerce. Through instruction-tuning a large language model …

Conditional generation with a question-answering blueprint

S Narayan, J Maynez, RK Amplayo… - Transactions of the …, 2023‏ - direct.mit.edu
The ability to convey relevant and faithful information is critical for many tasks in conditional
generation and yet remains elusive for neural seq-to-seq models whose outputs often reveal …

Domain adaptation with pre-trained transformers for query-focused abstractive text summarization

MTR Laskar, E Hoque, JX Huang - Computational Linguistics, 2022‏ - direct.mit.edu
Abstract The Query-Focused Text Summarization (QFTS) task aims at building systems that
generate the summary of the text document (s) based on the given query. A key challenge in …

[كتاب][B] Neural approaches to conversational information retrieval

J Gao, C **ong, P Bennett, N Craswell - 2023‏ - Springer
A conversational information retrieval (CIR) system is an information retrieval (IR) system
with a conversational interface, which allows users to interact with the system to seek …

WikiHowQA: A comprehensive benchmark for multi-document non-factoid question answering

V Bolotova-Baranova, V Blinov… - Proceedings of the …, 2023‏ - aclanthology.org
Answering non-factoid questions (NFQA) is a challenging task, requiring passage-level
answers that are difficult to construct and evaluate. Search engines may provide a summary …

Is it really long context if all you need is retrieval? towards genuinely difficult long context nlp

O Goldman, A Jacovi, A Slobodkin, A Maimon… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Improvements in language models' capabilities have pushed their applications towards
longer contexts, making long-context evaluation and development an active research area …