Papers Passage Retrieval
“Passage Retrieval” 태그가 달린 논문 292편 · 필터 해제
TabRank: Chain-of-Thought Distillation for Table Re-Rankers
The ability to retrieve relevant tables for answering questions is a key task for structured information retrieval. Multi-stage retrieval systems rely heavily on rerankers to refine candidate lists produced by efficient …
Information RetrievalNatural QuestionsPassage RetrievalTable RetrievalQuery-Aware Spreading Activation for Multi-Hop Retrieval over Knowledge Graphs
Retrieval-augmented generation built on knowledge graphs (Graph RAG) outperforms flat passage retrieval on multi-hop question answering by leveraging graph structure. In most existing systems, however, the question only …
Multi-hop Question AnsweringPassage RetrievalKnowledge GraphsThe Multilingual Curse at the Retrieval Layer: Evidence from Amharic
Multilingual retrieval increasingly underpins cross-lingual question answering and retrieval-augmented generation. Strong zero-shot scores on multilingual benchmarks are often taken as evidence that current encoders tran…
Cross-Lingual Question AnsweringPassage RetrievalGRASP: Graph Agentic Search over Propositions for Multi-hop Question Answering
Agentic retrieval improves multi-hop question answering by giving language models autonomy to iteratively gather evidence. Recent work augments these systems with knowledge graphs for structured traversal, but this combi…
Multi-hop Question AnsweringPassage RetrievalKnowledge GraphsThe Interference Gap: Comparing Retrieval Bounds in Human Memory and RAG Systems
How do retrieval bounds compare between human episodic memory and Retrieval-Augmented Generation (RAG) systems under semantic interference? We present a unified signal detection theory (SDT) framework that applies to bot…
Passage RetrievalIs It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval
Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an invention is disclosed in a prior art document. The process involves intrica…
Binary ClassificationPassage RetrievalBayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval
While Large Language Models (LLMs) exhibit exceptional zero-shot relevance modeling, their high computational cost necessitates framing passage retrieval as a budget-constrained global optimization problem. Existing appr…
Gaussian ProcessesPassage RetrievalActive LearningMulti-Faceted Self-Consistent Preference Alignment for Query Rewriting in Conversational Search
Conversational Query Rewriting (CQR) aims to rewrite ambiguous queries to achieve more efficient conversational search. Early studies have predominantly focused on the rewriting in isolation, ignoring the feedback from q…
Response GenerationPassage RetrievalBeyond Expression Similarity: Contrastive Learning Recovers Functional Gene Associations from Protein Interaction Structure
The Predictive Associative Memory (PAM) framework posits that useful relationships often connect items that co-occur in shared contexts rather than items that appear similar in embedding space. A contrastive MLP trained …
Contrastive LearningPassage RetrievalSpectral Tempering for Embedding Compression in Dense Passage Retrieval
Dimensionality reduction is critical for deploying dense retrieval systems at scale, yet mainstream post-hoc methods face a fundamental trade-off: principal component analysis (PCA) preserves dominant variance but underu…
Dimensionality ReductionPassage RetrievalLMEB: Long-horizon Memory Embedding Benchmark
Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchmarks, which narrowly focus on traditional passage retrieval and fail to …
Passage RetrievalAILS-NTUA at SemEval-2026 Task 8: Evaluating Multi-Turn RAG Conversations
We present the AILS-NTUA system for SemEval-2026 Task 8 (MTRAGEval), addressing all three subtasks of multi-turn retrieval-augmented generation: passage retrieval (A), reference-grounded response generation (B), and end-…
Response GenerationPassage RetrievalLearning to Evict from Key-Value Cache
The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Key-Value (KV) cache. Existing eviction or compression methods reduce cost…
Reinforcement LearningPassage RetrievalCross-Sensory Brain Passage Retrieval: Scaling Beyond Visual to Audio
Query formulation from internal information needs remains fundamentally challenging across all Information Retrieval paradigms due to cognitive complexity and physical impairments. Brain Passage Retrieval (BPR) addresses…
Information RetrievalPassage RetrievalSucceeding at Scale: Enterprise Retrieval Benchmark Construction and Index-Preserving Query Adaptation for Multi-Tenant Search
Large-scale multi-tenant retrieval systems generate extensive query logs but lack curated relevance labels for effective domain adaptation, resulting in substantial underutilized "dark data." This challenge is compounded…
parameter-efficient fine-tuningPassage RetrievalDomain AdaptationRADAR: Retrieval-Augmented Detector with Adversarial Refinement for Robust Fake News Detection
To efficiently combat the spread of LLM-generated misinformation, we present RADAR, a Retrieval-Augmented Detector with Adversarial Refinement for robust fake news detection. Our approach employs a generator that rewrite…
Fake News DetectionPassage RetrievalBlending Learning to Rank and Dense Representations for Efficient and Effective Cascades
We investigate the exploitation of both lexical and neural relevance signals for ad-hoc passage retrieval. Our exploration involves a large-scale training dataset in which dense neural representations of MS-MARCO queries…
Passage RetrievalLinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora
Retrieval-Augmented Generation (RAG) is widely used to mitigate hallucinations of Large Language Models (LLMs) by leveraging external knowledge. While effective for simple queries, traditional RAG systems struggle with l…
Relation ExtractionPassage RetrievalKnowledge GraphsRAGuard: A Novel Approach for in-context Safe Retrieval Augmented Generation for LLMs
Accuracy and safety are paramount in Offshore Wind (OSW) maintenance, yet conventional Large Language Models (LLMs) often fail when confronted with highly specialised or unexpected scenarios. We introduce RAGuard, an enh…
Passage RetrievalCLAP: Coreference-Linked Augmentation for Passage Retrieval
Large Language Model (LLM)-based passage expansion has shown promise for enhancing first-stage retrieval, but often underperforms with dense retrievers due to semantic drift and misalignment with their pretrained semanti…
Passage Retrieval