Search: “retrieval”

Differentiable Faithfulness Alignment for Cross-Model Circuit Transfer

arXiv:2604.24302v1 Announce Type: new Abstract: Mechanistic interpretability has made it possible to localize circuits underlying specific behaviors in language models, but existing methods are expens

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Agents

Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies

DGX agent

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

agentsarxiv-cs-ai

28 Apr 2026

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Explaining Sources of Uncertainty in Automated Fact-Checking

arXiv:2505.17855v2 Announce Type: replace Abstract: Understanding sources of a model's uncertainty regarding its predictions is crucial for effective human-AI collaboration. Prior work proposes using

researcharxiv-cs-cl

Graph Memory Transformer (GMT)

arXiv:2604.23862v1 Announce Type: cross Abstract: We investigate whether the Feed-Forward Network (FFN) sublayer in a decoder-only transformer can be replaced by an explicit learned memory graph while

Applications

Human-1 by Josh Talks: A Full-Duplex Conversational Modeling Framework in Hindi using Real-World Conversations

arXiv:2604.23295v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems re

applicationsarxiv-cs-ai

Information-Theoretic Measures in AI: A Practical Decision Guide

arXiv:2604.23716v1 Announce Type: new Abstract: Information-theoretic (IT) measures are ubiquitous in artificial intelligence: entropy drives decision-tree splits and uncertainty quantification, cross

LEGO: An LLM Skill-Based Front-End Design Generation Platform

arXiv:2604.23355v1 Announce Type: new Abstract: Existing LLM-based EDA agents are often isolated task-specific systems. This leads to repeated engineering effort and limited reuse of successful design

LLM-Guided Agentic Floor Plan Parsing for Accessible Indoor Navigation of Blind and Low-Vision People

arXiv:2604.23970v1 Announce Type: new Abstract: Indoor navigation remains a critical accessibility challenge for the blind and low-vision (BLV) individuals, as existing solutions rely on costly per-bu

MERIT: Modular Framework for Multimodal Misinformation Detection with Web-Grounded Reasoning

arXiv:2510.17590v2 Announce Type: replace Abstract: We present MERIT, an inference-time modular framework for multimodal misinformation detection that decomposes verification into four specialized mod

safetyarxiv-cs-ai

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

arXiv:2604.23539v1 Announce Type: new Abstract: The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Mode

Multi-view Graph Convolutional Network with Fully Leveraging Consistency via Granular-ball-based Topology Construction, Feature Enhancement and Interactive Fusion

arXiv:2603.26729v2 Announce Type: replace-cross Abstract: The effective utilization of consistency is crucial for multi-view learning. GCNs leverage node connections to propagate information across th

MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning

arXiv:2604.24186v1 Announce Type: cross Abstract: Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While Large Language Models (LLMs) have shown strong capab

safetyarxiv-cs-ai

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning

arXiv:2601.03790v3 Announce Type: replace-cross Abstract: Neologism-aware machine translation aims to translate source sentences containing neologisms into target languages. This field remains underex

'Noisier' Noise Contrastive Eestimation is (Almost) Maximum Likelihood

arXiv:2405.16730v2 Announce Type: replace-cross Abstract: Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing chal

Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface

arXiv:2604.24415v1 Announce Type: cross Abstract: Quantitative analysis of the kinematic chain in sports motion is essential for performance evaluation and injury prevention. Conventional methods such

researcharxiv-cs-cv

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

arXiv:2604.23148v1 Announce Type: new Abstract: The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In su

Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings

arXiv:2604.24597v1 Announce Type: cross Abstract: We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using qua

Query2Diagram: Answering Developer Queries with UML Diagrams

arXiv:2604.23816v1 Announce Type: cross Abstract: Software documentation frequently becomes outdated or fails to exist entirely, yet developers need focused views of their codebase to understand compl

RaV-IDP: A Reconstruction-as-Validation Framework for Faithful Intelligent Document Processing

arXiv:2604.23644v1 Announce Type: cross Abstract: Intelligent document processing pipelines extract structured entities (tables, images, and text) from documents for use in downstream systems such as

Resource-Lean Lexicon Induction for German Dialects

arXiv:2604.23824v1 Announce Type: new Abstract: Automatic induction of high-quality dictionaries is essential for building lexical resources, yet low-resource languages and dialects pose several chall

Local Ai

Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems

arXiv:2602.04120v2 Announce Type: replace-cross Abstract: Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most

local-aiarxiv-cs-ai

SeaEvo: Advancing Algorithm Discovery with Strategy Space Evolution

arXiv:2604.24372v1 Announce Type: cross Abstract: LLM-guided evolutionary search has emerged as a promising paradigm for automated algorithm discovery, yet most systems track search progress primarily

Shape: A Self-Supervised 3D Geometry Foundation Model for Industrial CAD Analysis

model-releasesarxiv-cs-cv

arXiv:2604.22826v1 Announce Type: new Abstract: Industrial CAD workflows require robust, generalizable 3D geometric representations supporting accuracy and explainability. We introduce Shape, a self-s

Tutorials

SRL-CLIP: Efficient CLIP Video Adaptation via Structured Semantic Role Labels

arXiv:2401.07669v2 Announce Type: replace Abstract: Adapting CLIP for videos has gained popularity due to its semantic and rich representation. While CLIP is a good starting point, it typically underg

tutorialsarxiv-cs-cv

Tutorials

Survey in Characterizing Semantic Change

arXiv:2402.19088v5 Announce Type: replace-cross Abstract: Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words

tutorialsarxiv-cs-ai

Test of Time: Rethinking Temporal Signal of Benchmark Contamination

arXiv:2509.00072v3 Announce Type: replace Abstract: Post-cutoff performance decay has been widely interpreted as a temporal signal for benchmark contamination. We critically examine this belief and de

The Override Gap: A Magnitude Account of Knowledge Conflict Failure in Hypernetwork-Based Instant LLM Adaptation

arXiv:2604.23750v1 Announce Type: cross Abstract: Hypernetwork-based methods such as Doc-to-LoRA internalize a document into an LLM's weights in a single forward pass, but they fail systematically on

Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement

arXiv:2601.02018v2 Announce Type: replace Abstract: Segment Anything Models (SAMs), known for their exceptional zero-shot segmentation performance, have garnered significant attention in the research

safetyarxiv-cs-cv

Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach

arXiv:2604.23090v1 Announce Type: new Abstract: Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language

Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations

arXiv:2604.24562v1 Announce Type: new Abstract: Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requir

Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills

arXiv:2603.25158v4 Announce Type: replace Abstract: Equipping Large Language Model (LLM) agents with domain-specific skills is critical for tackling complex tasks. Yet, manual authoring creates a seve

TSAssistant: A Human-in-the-Loop Agentic Framework for Automated Target Safety Assessment

arXiv:2604.23938v1 Announce Type: new Abstract: Target Safety Assessment (TSA) requires systematic integration of heterogeneous evidence, including genetic, transcriptomic, target homology, pharmacolo

safetyarxiv-cs-cl

Uncertainty Quantification for LLM Function-Calling

arXiv:2604.22985v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed to autonomously solve real-world tasks. A key ingredient for this is the LLM Function-Calling par

agentsarxiv-cs-cl

Tutorials

When AI reviews science: Can we trust the referee?

arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s

tutorialsarxiv-cs-ai

Applications

When Silence Matters: The Impact of Irrelevant Audio on Text Reasoning in Large Audio-Language Models

arXiv:2510.00626v3 Announce Type: replace-cross Abstract: Large audio-language models (LALMs) unify speech and text processing, but their robustness in noisy real-world settings remains underexplored.

applicationsarxiv-cs-cl

Local Ai

An LLM-Driven Closed-Loop Autonomous Learning Framework for Robots Facing Uncovered Tasks in Open Environments

arXiv:2604.22199v1 Announce Type: cross Abstract: Autonomous robots operating in open environments need the ability to continuously handle tasks that are not covered by predefined local methods. Howev

local-aiarxiv-cs-ai

Atlas-Alignment: Making Interpretability Transferable Across Language Models

arXiv:2510.27413v2 Announce Type: replace-cross Abstract: Interpretability is crucial for building safe, reliable, and controllable language models, yet existing interpretability pipelines remain cost

Hardware

Beyond Land Surface Temperature: Explainable Spatial Machine Learning Reveals Urban Morphology Effects on Human-Centric Heat Stress

arXiv:2604.22433v1 Announce Type: new Abstract: Heat exposure connects the built environment and public health, directly shaping the livability and sustainability of urban areas. Understanding the spa

hardwarearxiv-cs-lg

ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding

arXiv:2604.22333v1 Announce Type: cross Abstract: Rapid situational awareness is critical in post-disaster response. While remote sensing damage assessment is evolving from pixel-level change detectio

Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations

arXiv:2604.22207v1 Announce Type: cross Abstract: Due to the textual and repetitive nature of many Requirements Engineering (RE) artefacts, Large Language Models (LLMs) have proven useful to automate

HACHIMI: Scalable and Controllable Student Persona Generation via Orchestrated Agents

arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles

agentsarxiv-cs-cl

How Large Language Models Balance Internal Knowledge with User and Document Assertions

arXiv:2604.22193v1 Announce Type: new Abstract: Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from

safetyarxiv-cs-cl

LLMs as Assessors: Right for the Right Reason?

arXiv:2601.08919v2 Announce Type: replace-cross Abstract: A good deal of recent research has focused on how Large Language Models (LLMs) may be used as judges in place of humans to evaluate the qualit

Navigating Large-Scale Document Collections: MuDABench for Multi-Document Analytical QA

arXiv:2604.22239v1 Announce Type: cross Abstract: This paper introduces the task of analytical question answering over large, semi-structured document collections. We present MuDABench, a benchmark fo

PL-MTEB: Polish Massive Text Embedding Benchmark

arXiv:2405.10138v2 Announce Type: replace Abstract: In this paper, we introduce the Polish Massive Text Embedding Benchmark (PL-MTEB), a comprehensive benchmark for text embeddings in the Polish langu

Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization

arXiv:2604.22345v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong implicit personalization ability, yet most existing approaches treat this behavior as a black box, relying o

researcharxiv-cs-cl

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning

arXiv:2604.22076v1 Announce Type: cross Abstract: Large language models (LLMs) often memorize private information during training, raising serious privacy concerns. While machine unlearning has emerge

researcharxiv-cs-cl