Papers Query-focused Summarization
“Query-focused Summarization” 태그가 달린 논문 36편 · 필터 해제
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAG
Retrieval-Augmented Generation (RAG) enables large language models to provide more precise and pertinent responses by incorporating external knowledge. In the Query-Focused Summarization (QFS) task, GraphRAG-based approa…
DiversityQuery-focused SummarizationRAGResponse Generation+2DETQUS: Decomposition-Enhanced Transformers for QUery-focused Summarization
Query-focused tabular summarization is an emerging task in table-to-text generation that synthesizes a summary response from tabular data based on user queries. Traditional transformer-based approaches face challenges du…
DecoderLanguage ModelingLanguage ModellingLarge Language Model+3Unstructured Evidence Attribution for Long Context Query Focused Summarization
Large language models (LLMs) are capable of generating coherent summaries from very long contexts given a user query. Extracting and properly citing evidence spans could help improve the transparency and reliability of t…
Query-focused SummarizationReasoning-Aware Query-Focused Summarization over Multi-Table Data
Query-focused summarization over multi-table data is a challenging yet critical task for extracting precise and relevant information from structured data. Existing methods often rely on complex preprocessing steps and st…
Logical ReasoningQuery-focused SummarizationDoes This Summary Answer My Question? Modeling Query-Focused Summary Readers with Rational Speech Acts
Query-focused summarization (QFS) is the task of generating a summary in response to a user-written query. Despite its user-oriented nature, there has been limited work in QFS in explicitly considering a user's understan…
Query-focused SummarizationText GenerationLearning to Rank Salient Content for Query-focused Summarization
This study examines the potential of integrating Learning-to-Rank (LTR) with Query-focused Summarization (QFS) to enhance the summary relevance via content prioritization. Using a shared secondary decoder with the summar…
DecoderLearning-To-RankQuery-focused SummarizationBeyond Relevant Documents: A Knowledge-Intensive Approach for Query-Focused Summarization using Large Language Models
Query-focused summarization (QFS) is a fundamental task in natural language processing with broad applications, including search engines and report generation. However, traditional approaches assume the availability of r…
Language ModelingLanguage ModellingLarge Language ModelQuery-focused Summarization+1IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization
Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and personalization. With the advent of large language models (LLMs), shows their im…
Document SummarizationQuery-focused SummarizationFrom Local to Global: A Graph RAG Approach to Query-Focused Summarization
The use of retrieval-augmented generation (RAG) to retrieve relevant information from an external knowledge source enables large language models (LLMs) to answer questions over private and/or previously unseen document c…
Query-focused SummarizationQuestion AnsweringRAGRetrieval+1WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations
Enhancing the attribution in large language models (LLMs) is a crucial task. One feasible approach is to enable LLMs to cite external sources that support their generations. However, existing datasets and evaluation meth…
Query-focused SummarizationContext-aware Decoding Reduces Hallucination in Query-focused Summarization
Query-focused summarization (QFS) aims to provide a summary of a single document/multi documents that can satisfy the information needs of a given query. It is useful for various real-world applications, such as abstract…
HallucinationLanguage ModellingLarge Language ModelNews Summarization+4Reinforcement Replaces Supervision: Query focused Summarization using Deep Reinforcement Learning
Query-focused Summarization (QfS) deals with systems that generate summaries from document(s) based on a query. Motivated by the insight that Reinforcement Learning (RL) provides a generalization to Supervised Learning (…
Deep Reinforcement LearningLong Form Question AnsweringQuery-focused SummarizationQuestion Answering+5QontSum: On Contrasting Salient Content for Query-focused Summarization
Query-focused summarization (QFS) is a challenging task in natural language processing that generates summaries to address specific queries. The broader field of Generative Information Retrieval (Gen-IR) aims to revoluti…
Answer GenerationContrastive LearningInformation RetrievalQuery-focused Summarization+1QuOTeS: Query-Oriented Technical Summarization
Abstract. When writing an academic paper, researchers often spend considerable time reviewing and summarizing papers to extract relevant citations and data to compose the Introduction and Related Work sections. To addres…
Extractive SummarizationInformation RetrievalQuery-focused SummarizationRetrievalPeek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering
The integration of multi-document pre-training objectives into language models has resulted in remarkable improvements in multi-document downstream tasks. In this work, we propose extending this idea by pre-training a ge…
Query-focused SummarizationQuestion AnsweringSentenceText GenerationQTSumm: Query-Focused Summarization over Tabular Data
People primarily consult tables to conduct data analysis or answer specific questions. Text generation systems that can provide accurate table summaries tailored to users' information needs can facilitate more efficient …
Query-focused SummarizationTable-to-Text GenerationText GenerationLMGQS: A Large-scale Dataset for Query-focused Summarization
Query-focused summarization (QFS) aims to extract or generate a summary of an input document that directly answers or is relevant to a given query. The lack of large-scale datasets in the form of documents, queries, and …
DiversityLanguage ModelingLanguage ModellingQuery-focused Summarization+1Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation
While conditional generation models can now generate natural language well enough to create fluent text, it is still difficult to control the generation process, leading to irrelevant, repetitive, and hallucinated conten…
Query-focused SummarizationText GenerationA Lightweight Constrained Generation Alternative for Query-focused Summarization
Query-focused summarization (QFS) aims to provide a summary of a document that satisfies information need of a given query and is useful in various IR applications, such as abstractive snippet generation. Current QFS app…
Language ModelingLanguage ModellingLarge Language ModelQuery-focused Summarization+1Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization
The CrisisFACTS Track aims to tackle challenges such as multi-stream fact-finding in the domain of event tracking; participants' systems extract important facts from several disaster-related events while incorporating th…
DiversityExtractive SummarizationQuery-focused SummarizationQuestion Answering+2