Knowledge catalogue
arXiv:2604.20487v1 Announce Type: cross Abstract: Large language models (LLMs) encode knowledge in parametric weights, making it costly to update or extend without retraining. Retrieval-augmented gene
arXiv:2604.20261v1 Announce Type: new Abstract: Automated feature generation extracts informative features from raw tabular data without manual intervention and is crucial for accurate, generalizable
arXiv:2604.20146v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving
arXiv:2604.20417v1 Announce Type: cross Abstract: We introduce Semantic Recall, a novel metric to assess the quality of approximate nearest neighbor search algorithms by considering only semantically
arXiv:2604.19793v1 Announce Type: new Abstract: LLM agents must select tools from large API libraries and order them correctly. Existing methods use semantic similarity for both retrieval and ordering
arXiv:2505.07849v2 Announce Type: replace-cross Abstract: Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language
arXiv:2604.20117v1 Announce Type: new Abstract: Constructivist epistemology argues that knowledge is actively constructed rather than passively copied. Despite the generative nature of Large Language
arXiv:2604.19137v1 Announce Type: new Abstract: Knowledge Graph (KG) can effectively integrate valuable information from massive data, and thus has been rapidly developed and widely used in many field
Traditional data catalogs were built as manual inventories for technical users, focusing on table structures rather than the deep context that AI agents need. When agents lack business semantics and d
arXiv:2602.11161v2 Announce Type: replace-cross Abstract: The web's information ecosystem demands fact-checking systems that are both scalable and epistemically trustworthy. Automated approaches offer
arXiv:2510.00861v2 Announce Type: replace Abstract: While search-augmented large language models (LLMs) exhibit impressive capabilities, their reliability in complex multi-hop reasoning remains limite
arXiv:2509.12539v2 Announce Type: replace-cross Abstract: We present LEAF ('Lightweight Embedding Alignment Framework'), a knowledge distillation framework for text embedding models. A key distinguish
arXiv:2604.17052v1 Announce Type: new Abstract: Streaming video reasoning requires models to operate in a setting where history grows without bound while meaningful evidence remains scarce. In such a
arXiv:2601.15724v2 Announce Type: replace Abstract: Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning
arXiv:2604.17475v1 Announce Type: cross Abstract: Small Vision-Language Models (SVLMs) are efficient task controllers but often suffer from visual brittleness and poor tool orchestration. They typical
arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec
arXiv:2604.15672v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates language model inference by drafting tokens from a cheap proposal model and verifying them against an expensive
arXiv:2604.15646v1 Announce Type: new Abstract: Clinicians exploring oncology trial repositories often need ad-hoc, multi-constraint queries over biomarkers, endpoints, interventions, and time, yet wr
arXiv:2604.13042v1 Announce Type: cross Abstract: Semantic data harmonisation is a central requirement in the ILIAD project, where heterogeneous environmental data must be harmonised according to the
arXiv:2604.15124v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) is central to diabetes care, but explaining CGM patterns clearly and empathetically remains time-intensive. Evidence
arXiv:2601.21262v3 Announce Type: replace Abstract: Although Multimodal Large Language Models (MLLMs) have shown remarkable potential in Visual Document Retrieval (VDR) through generating high-quality
arXiv:2604.15244v1 Announce Type: new Abstract: Speculative decoding (SD) accelerates large language model inference by allowing a lightweight draft model to propose outputs that a stronger target mod
arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the
arXiv:2601.13115v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through na
arXiv:2512.02697v3 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images that visually correspond to a query image. However, the trad
arXiv:2604.13579v1 Announce Type: new Abstract: Conventional Retrieval-Augmented Generation (RAG) systems often struggle with complex multi-hop queries over long documents due to their single-pass ret
AetherMind is a locally-run personal memory system built by a Reddit user (r/ollama) that leverages Ollama with the `qwen2.5:7b` model and Retrieval-Augmented Generation (RAG) to allow users to query
arXiv:2604.05821v2 Announce Type: replace Abstract: Existing multilingual embedding models often encounter challenges in cross-lingual scenarios due to imbalanced linguistic resources and less conside
arXiv:2604.12967v1 Announce Type: new Abstract: Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches
arXiv:2604.12285v1 Announce Type: new Abstract: To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining
arXiv:2604.12081v1 Announce Type: new Abstract: Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the con
arXiv:2602.23061v3 Announce Type: replace-cross Abstract: Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and
arXiv:2604.12184v1 Announce Type: new Abstract: TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a
Databricks explores how agentic AI systems can reason over both structured data (such as tables and databases) and unstructured data (such as documents and text) to answer complex business questions.
arXiv:2604.10874v1 Announce Type: cross Abstract: Adverse Outcome Pathways (AOPs) are an important knowledge framework in toxicological research and risk assessment. In recent years, large language mo
arXiv:2604.09690v1 Announce Type: new Abstract: Jaguar re-identification (re-ID) from citizen-science imagery can look strong on standard retrieval metrics while still relying on the wrong evidence, s
arXiv:2604.11539v1 Announce Type: cross Abstract: Human perception of visual similarity is inherently adaptive and subjective, depending on the users' interests and focus. However, most image retrieva
arXiv:2604.10426v1 Announce Type: cross Abstract: Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While
arXiv:2604.10741v1 Announce Type: cross Abstract: Recent agentic search frameworks enable deep research via iterative planning and retrieval, reducing hallucinations and enhancing factual grounding. H
arXiv:2604.11043v1 Announce Type: new Abstract: Unified multimodal embedding spaces underpin practical applications such as cross-modal retrieval and zero-shot recognition. In many real deployments, h
arXiv:2601.08209v3 Announce Type: replace Abstract: In domains such as materials science, biomedicine, and finance, high-stakes deployment of large language models (LLMs) requires injecting private, d
A Reddit user on r/StableDiffusion built a locally-running RAG (Retrieval-Augmented Generation) engine designed to eliminate the need for manually crafting lengthy, model-specific image generation pro
arXiv:2603.23516v2 Announce Type: replace-cross Abstract: Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in
arXiv:2604.10604v1 Announce Type: cross Abstract: Standard dense retrievers lack a native calculus for multi-atom logical constraints. We introduce Neuro-Symbolic Fuzzy Logic (NSFL), a framework that
arXiv:2604.09588v1 Announce Type: new Abstract: Modern AI agents suffer from a fundamental identity problem: when context windows overflow and conversation histories are summarized, agents experience
arXiv:2512.06879v3 Announce Type: replace-cross Abstract: We present extsc{WisPaper}, an end-to-end agent system that transforms how researchers discover, organize, and track academic literature. The
arXiv:2508.04038v2 Announce Type: replace Abstract: Motion sensor time-series are central to Human Activity Recognition (HAR), yet conventional approaches are constrained to fixed activity sets and ty
arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com
This Reddit post from r/ChatGPT discusses the trade-offs between retrieving documentation via an MCP (Model Context Protocol) server versus using traditional web search within AI workflows. The core c
arXiv:2604.08952v1 Announce Type: new Abstract: Document Question Answering (DQA) involves generating answers from a document based on a user's query, representing a key task in document understanding
arXiv:2508.06869v4 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) demonstrate exceptional performance in vision-language tasks, yet their processing of long videos is
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Auto-generated index of all models mentioned across the wiki.
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arXiv:2604.08504v1 Announce Type: cross Abstract: We initiate the study of language generation in the limit, a model recently introduced by Kleinberg and Mullainathan [KM24], under the constraint of d
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arXiv:2604.07490v1 Announce Type: new Abstract: Representation learning for geospatial and spatio-temporal data plays a critical role in enabling general-purpose geospatial intelligence. Recent geospa
I was unable to retrieve the specific Reddit post at the provided URL (reddit.com/r/ChatGPT/comments/1sh9hma/lighter_joke/), as it did not appear in the search results. The search only returned gen...
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arXiv:2604.05268v2 Announce Type: replace-cross Abstract: Multi-modal retrieval-augmented generation (MM-RAG) relies heavily on re-rankers to surface the most relevant evidence for image-question quer