Daily edition · Information Retrieval
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44 articles · 3 sources · 44 papers ·
Top topics: Information Retrieval · AI · AI Research
arXiv:2605.18770v3 Announce Type: replace Abstract: Public commercial registries are formally open, yet their practical analysis remains difficult because relevant facts are scattered across millions of records that…
arXiv:2607.21951v3 Announce Type: replace Abstract: This paper investigates the adversarial manipulation of the ranked recommendations produced by web-augmented large language models (LLMs). When an LLM answers a…
arXiv:2609.37469v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) grounds large language models in external sources, but retrieved passages often name the right entities without providing the facts…
arXiv:2609.35904v1 Announce Type: new Abstract: This report presents the web agent system developed for the WebRetriever Challenge. The system follows a structuredinteraction- first strategy, using semantic webpage…
arXiv:2609.37749v1 Announce Type: new Abstract: The increasing importance of Information Retrieval (IR) in managing large datasets has highlighted significant limitations in traditional keyword-based search systems.…
arXiv:2609.38155v1 Announce Type: cross Abstract: Answering questions about long videos often requires connecting events involving the same objects across hours or days. Chronological descriptions and text-derived…
arXiv:2609.36059v1 Announce Type: cross Abstract: Long-term memory lets an LLM assistant use a history it can no longer reread, and most memory systems build it by rewriting conversations into facts, graphs or typed…
arXiv:2609.34951v2 Announce Type: replace-cross Abstract: In 2023, AI models answered from training data and hallucinated when it ran out, and businesses were told to seed that knowledge. Models' training knowledge has…
arXiv:2609.36946v1 Announce Type: new Abstract: ZS-CIR aims to retrieve a target image from a reference image and a modification text without paired supervision, typically by encoding composed queries as text-dominant…
arXiv:2609.36849v1 Announce Type: cross Abstract: Safety-aligned language models are commonly deployed as multi-turn assistants, which lets adversaries spread unsafe intent across several user turns instead of a single…
arXiv:2609.36340v1 Announce Type: cross Abstract: High-stakes advisory domains such as medical aesthetics, legal consultation, and educational planning exhibit a two-phase structure. The early phase requires empathetic…
arXiv:2609.37472v1 Announce Type: new Abstract: Behavioral tests measure how a language model reads evidence. We ask whether those measurements help choose a recommendation interface. We evaluate six small…
arXiv:2512.00329v2 Announce Type: replace-cross Abstract: Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose an approach that recasts the task as automated…
arXiv:2609.38099v1 Announce Type: new Abstract: Turning decoder-only large language models (LLMs) into strong dense retrievers typically requires some form of retriever training. In this paper, we ask whether LLMs can…
arXiv:2609.37911v1 Announce Type: new Abstract: Scientific queries are often brief, while relevant papers use specialized vocabulary. Generated query expansion can bridge this mismatch, but earlier work suggests that…
arXiv:2609.35782v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) retrieves candidate evidence and sends only a limited top-ranked subset, the top-k context, to a generator. In financial question…
arXiv:2609.37311v1 Announce Type: cross Abstract: Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative agents autonomously…
arXiv:2603.28773v2 Announce Type: replace Abstract: Large language models (LLMs) frequently generate confident yet factually incorrect content when used for language generation (a phenomenon often known as…
arXiv:2609.37226v1 Announce Type: cross Abstract: Answering questions and completing tasks over large document collections often requires connecting evidence spread across multiple documents, such as a project's…
arXiv:2609.37183v1 Announce Type: new Abstract: Industrial recommendation ranking models typically scale along two modeling axes: feature interaction over heterogeneous user, item, context, and cross features, and…
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