Information Retrieval
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Related Articles from SNS
MIMO: Multilingual Information Retrieval via Monolingual Objectives
Announce Type: new Abstract: Multilingual Information Retrieval (MLIR) reflects real-world search environments in which queries and relevant documents may appear in different languages within a mixed-language corpus. However, existing embedding models are primarily optimized for Multi-Monolingual retrieval and their performance often degrades in MLIR settings. Moreover, directly applying conventional contrastive learning to MLIR can exacerbate language clustering and expose a trade-off...
Attention Calibration for Position-Fair Dense Information Retrieval
arXiv:2606.02737v1 Announce Type: new Abstract: Dense retrieval models exhibit positional bias: retrieval effectiveness degrades when relevant information appears later in a passage (Zeng et al., 2025). We ask whether this bias can be reduced at inference time, without retraining and without sacrificing overall retrieval effectiveness. To this end, we adapt inference-time attention calibration (Schuhmacher et al., 2026) to downstream retrieval and extend it with a strength coefficient lambda...
CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval
arXiv:2506.11066v3 Announce Type: replace Abstract: Code retrieval is essential in modern software development, as it boosts code reuse and accelerates debugging. However, current benchmarks primarily emphasize functional relevance while neglecting critical dimensions of software quality. Motivated by this gap, we introduce CoQuIR, the first large-scale, multilingual benchmark specifically designed to evaluate quality-aware code retrieval across four key dimensions: correctness, efficiency,...
SatIR: Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching
Announce Type: replace Abstract: Many important retrieval problems are not merely problems of semantic similarity, but problems of constraint satisfaction: a retrieved item should be topically relevant to a query and satisfy explicit requirements involving negation, temporal conditions, numeric thresholds, exceptions, ontological relations, and incomplete evidence. We study this challenge in clinical trial matching, a high-stakes test bed where a useful trial must both address a patient's...
Structured Semantic Information Helps Retrieve Better Examples for In-Context Learning Applied to Few-Shot Relation Extraction
Announce Type: replace Abstract: This paper presents several strategies to automatically obtain additional examples for in-context learning, effectively transforming relation extraction from a 1-shot to a few-shot setting. Specifically, we introduce a novel strategy for example selection, in which new examples are selected based on the similarity of their underlying syntactic-semantic structure to the provided 1-shot example. We show that our strategy results in complementary word choices...
Automating Information Extraction and Retrieval for Industrial Spare Parts Pooling
arXiv:2606.03367v1 Announce Type: new Abstract: Maintenance organizations in manufacturing try to avoid downtime and unnecessary purchasing by reusing existing assets, but the main obstacle is not a lack of parts but a lack of actionable visibility across sites and partners. Inventories are distributed, described with inconsistent naming conventions, and contain duplicates and partially specified references, so the right part often exists somewhere but remains effectively undiscoverable. The...
Towards Retrieving Interaction Spaces for Agentic Search
Announce Type: new Abstract: Retrieval for search agents is still inherited from non-agentic information retrieval: a retriever ranks the corpus and the agent reads a small set of returned documents. Recent direct corpus interaction (DCI) work shows that agents can instead interact with the raw corpus through shell tools such as grep and file reads. But unbounded interaction does not scale: every broad shell command is a scan over the whole corpus, and latency degrades sharply as the corpus...
RISE: A Rust Library for Inverted Index Search Engines
arXiv:2606.07187v1 Announce Type: new Abstract: Inverted indexes are a crucial data structure for efficient information retrieval in large text corpora. They enable fast full-text search by mapping each term to the documents in which it appears, on top of which efficient algorithms quickly retrieve the documents relevant to a user query. We present RISE, a novel inverted index library implemented in Rust, designed to deliver high performance and efficiency for information retrieval tasks.
Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)
arXiv:2606.08936v1 Announce Type: new Abstract: This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI\&AS), which examined how GenAI is reshaping academic search systems and research practices. The workshop brought together researchers in human information interaction and information retrieval to explore key challenges and opportunities in designing and evaluating future academic search systems that integrate GenAI, moving beyond traditional document...
Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking
arXiv:2606.01240v1 Announce Type: new Abstract: The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augmented generation (RAG). The RAG system assists LLM generation by retrieving chunks of query-fit supplementary knowledge from an external database. Conventional RAG systems, however, suffer from information insufficiency due to two factors, which are intent-agnostic retrieval and information...