Challenge: a document retrieval system fails to deliver diverse and direct responses to controversial questions . classical document retrievals provide a ranked list of references to relevant but not necessarily trustworthy web documents .
Approach: They propose a perspective-oriented document retrieval paradigm to address these challenges . they propose sponses with different perspectives within topically-related web documents .
Outcome: The proposed system is based on a user survey and a prototype . it will be used to assess the utility and understanding of the system .

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Open-World Evaluation for Retrieving Diverse Perspectives (2025.naacl-long)

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Challenge: Existing retrieval systems only cover diverse perspectives on 33.74% of the examples . existing systems only focus on relevance to the question, ignoring diversity.
Approach: They build a Benchmark for Retrieval Diversity for Subjective questions (BERDS) based on a question and diverse perspectives associated with the question . they evaluate retrievers paired with a corpus to determine whether each document contains a perspective .
Outcome: The proposed approach improves retrieval diversity on complex questions . existing retrieval systems only cover diverse perspectives on 33.74% of the examples .
Towards Multi-Document Question Answering in Scientific Literature: Pipeline, Dataset, and Evaluation (2025.findings-emnlp)

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Challenge: Existing QA systems do not strictly enforce cross-document synthesis or exploit the explicit inter-paper structure that links sources.
Approach: They propose a pipeline methodology for constructing a multi-document academic QA dataset . they detect communities based on citation networks and leverage Large Language Models .
Outcome: The proposed method generates QA pairs related to multi-document content automatically and forms coherent communities based on citation networks and large language models.
Multi-View Document Representation Learning for Open-Domain Dense Retrieval (2022.acl-long)

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Challenge: Existing methods for dense retrieval are hard to match with multiple views.
Approach: They propose a multi-view document representation learning framework to generate multiple embeddings through viewers to represent documents and enforce them to align with different queries.
Outcome: The proposed method outperforms recent works and achieves state-of-the-art results.
PerSphere: A Comprehensive Framework for Multi-Faceted Perspective Retrieval and Summarization (2025.acl-long)

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Challenge: Experimental results show that the main challenge lies in long context and perspective extraction.
Approach: They propose a benchmark to facilitate multi-faceted perspective retrieval and summarization . they propose measurable metrics to evaluate the comprehensiveness of the retrieval pipeline .
Outcome: The proposed system breaks free from information silos by combining two opposing claims . it can be used to extract multiple perspectives and improve performance on the platform .
Seeing Things from a Different Angle:Discovering Diverse Perspectives about Claims (N19-1)

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Challenge: a number of fact checking techniques are used to identify and eliminate biases in text data.
Approach: They propose to use search engines to expand and diversify a dataset of claims, perspectives and evidence to address a selection bias.
Outcome: The proposed approach outperforms existing methods in a language understanding task.
A Comprehensive Graph Framework for Question Answering with Mode-Seeking Preference Alignment (2025.findings-acl)

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Challenge: Existing studies struggle with achieving global understanding of large language models . GraphMPA is a graph-based framework with mode-seeking preference alignment .
Approach: They propose a graph-based framework with mode-seeking preference alignment to improve model outputs.
Outcome: The proposed framework constructs a hierarchical document graph mimicking human cognitive processes for information understanding and synthesis.
A Survey on Open Information Extraction (C18-1)

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Challenge: Existing approaches to open information extraction (Open IE) focus on narrow, well-defined requests over a predefined set of target relations on small, homogeneous corpora.
Approach: They propose to use unsupervised methods to extract all types of relations found in text . they propose to implement a system that can be automated to detect possible relations .
Outcome: The proposed approaches have been compared with existing methods and are based on the results of a literature review.
MultiConIR: Towards Multi-Condition Information Retrieval (2025.findings-emnlp)

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Challenge: MultiConIR is a benchmark designed to evaluate retrieval and reranking models under nuanced multi-condition query scenarios.
Approach: They propose a benchmark to evaluate retrieval and reranking models under nuanced multi-condition query scenarios.
Outcome: The proposed benchmark evaluates retrieval and reranking models under nuanced multi-condition query scenarios across five domains.
A Survey of Reasoning-Intensive Retrieval: Progress and Challenges (2026.acl-long)

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Challenge: Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting evidence, rather than semantic similarity.
Approach: They propose a taxonomy that categorizes methods based on where and how reasoning is integrated into the retrieval pipeline.
Outcome: The proposed method framework provides a detailed analysis of the current landscape and its trade-offs and practical applications.
XOR QA: Cross-lingual Open-Retrieval Question Answering (2021.naacl-main)

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Challenge: a dataset of 40k information-seeking questions across seven languages is used to answer multilingual question answering tasks.
Approach: They propose a task framework that allows questions from one language to be answered via answer content from another language.
Outcome: The proposed framework can be used to answer questions from one language to another . the dataset was built on 40K questions across 7 languages, but could not find same-language answers .

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