Search: “evaluation”

CI-Work: Benchmarking Contextual Integrity in Enterprise LLM Agents

model-releasesarxiv-cs-cl

arXiv:2604.21308v1 Announce Type: cross Abstract: Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a us

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CoFEE: Reasoning Control for LLM-Based Feature Discovery

DGX agent

arXiv:2604.21584v1 Announce Type: new Abstract: Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a tar

researcharxiv-cs-ai

24 Apr 2026

Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning

arXiv:2509.23744v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-m

Dementia classification from spontaneous speech using wrapper-based feature selection

arXiv:2502.03484v2 Announce Type: replace-cross Abstract: Dementia encompasses a group of syndromes that impair cognitive functions such as memory, reasoning, and the ability to perform daily activiti

researcharxiv-cs-lg

Do MLLMs Understand Pointing? Benchmarking and Enhancing Referential Reasoning in Egocentric Vision

arXiv:2604.21461v1 Announce Type: new Abstract: Egocentric AI agents, such as smart glasses, rely on pointing gestures to resolve referential ambiguities in natural language commands. However, despite

DryRUN: On the Role of Public Tests in LLM-Driven Code Generation

arXiv:2604.21598v1 Announce Type: cross Abstract: Multi-agent frameworks are widely used in autonomous code generation and have applications in complex algorithmic problem-solving. Recent work has add

agentsarxiv-cs-ai

Local Ai

DWTSumm: Discrete Wavelet Transform for Document Summarization

arXiv:2604.21070v1 Announce Type: new Abstract: Summarizing long, domain-specific documents with large language models (LLMs) remains challenging due to context limitations, information loss, and hall

local-aiarxiv-cs-cl

Effects of Swarm Size Variability on Operator Workload

arXiv:2604.21707v1 Announce Type: new Abstract: Real-world deployments of human--swarm teams depend on balancing operator workload to leverage human strengths without inducing overload. A key challeng

agentsarxiv-cs-ro

Enabling and Inhibitory Pathways of University Students' Willingness to Disclose AI Use: A Cognition-Affect-Conation Perspective

arXiv:2604.21733v1 Announce Type: new Abstract: The increasing integration of artificial intelligence (AI) in higher education has raised important questions regarding students' transparency in report

Local Ai

Frozen LLMs as Map-Aware Spatio-Temporal Reasoners for Vehicle Trajectory Prediction

arXiv:2604.21479v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated strong reasoning capabilities and attracted increasing research attention in the field of autono

local-aiarxiv-cs-cv

GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark

model-releasesarxiv-cs-cl

arXiv:2601.13711v2 Announce Type: replace Abstract: Authorship verification (AV) is the task of determining whether two texts were written by the same author and has been studied extensively, predomin

GRISP: Guided Recurrent IRI Selection over SPARQL Skeletons

arXiv:2604.21133v1 Announce Type: new Abstract: We present GRISP (Guided Recurrent IRI Selection over SPARQL Skeletons), a novel SPARQL-based question-answering method over knowledge graphs based on f

Local Ai

ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing

arXiv:2604.21280v1 Announce Type: new Abstract: On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropag

local-aiarxiv-cs-cv

Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning

arXiv:2603.27820v2 Announce Type: replace Abstract: Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanatio

agentsarxiv-cs-cl

Job Skill Extraction via LLM-Centric Multi-Module Framework

arXiv:2604.21525v1 Announce Type: new Abstract: Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (L

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

arXiv:2505.13527v3 Announce Type: replace-cross Abstract: Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to j

MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting

arXiv:2604.21489v1 Announce Type: cross Abstract: Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency d

Applications

Nonlinear Causal Discovery through a Sequential Edge Orientation Approach

arXiv:2506.05590v3 Announce Type: replace-cross Abstract: Recent advances have established the identifiability of a directed acyclic graph (DAG) under additive noise models (ANMs), spurring the develo

applicationsarxiv-cs-lg

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

arXiv:2604.21017v1 Announce Type: cross Abstract: Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precis

PanGuide3D: Cohort-Robust Pancreas Tumor Segmentation via Probabilistic Pancreas Conditioning and a Transformer Bottleneck

arXiv:2604.20981v1 Announce Type: cross Abstract: Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma

researcharxiv-cs-cv

Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance

arXiv:2604.21104v1 Announce Type: new Abstract: New geospatial foundation models introduce a new model architecture and pretraining dataset, often sampled using different notions of data diversity. Pe

Process Supervision via Verbal Critique Improves Reasoning in Large Language Models

arXiv:2604.21611v1 Announce Type: cross Abstract: Inference-time scaling for LLM reasoning has focused on three axes: chain depth, sample breadth, and learned step-scorers (PRMs). We introduce a fourt

RailVQA: A Benchmark and Framework for Efficient Interpretable Visual Cognition in Automatic Train Operation

arXiv:2603.27112v2 Announce Type: replace Abstract: As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and de

SafeRedirect: Defeating Internal Safety Collapse via Task-Completion Redirection in Frontier LLMs

arXiv:2604.20930v1 Announce Type: cross Abstract: Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion structu

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs

arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training

researcharxiv-cs-lg

Hardware

Stream2LLM: Overlap Context Streaming and Prefill for Reduced Time-to-First-Token (TTFT)

arXiv:2604.16395v2 Announce Type: replace-cross Abstract: Context retrieval systems for LLM inference face a critical challenge: high retrieval latency creates a fundamental tension between waiting fo

hardwarearxiv-cs-ai

Structured Visual Narratives Undermine Safety Alignment in Multimodal Large Language Models

arXiv:2603.21697v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) extend text-only LLMs with visual reasoning, but also introduce new safety failure modes under visual

StyleID: A Perception-Aware Dataset and Metric for Stylization-Agnostic Facial Identity Recognition

arXiv:2604.21689v1 Announce Type: cross Abstract: Creative face stylization aims to render portraits in diverse visual idioms such as cartoons, sketches, and paintings while retaining recognizable ide

TAPO-Description Logic for Information Behavior: Refined OBoxes, Inference, and Categorical Semantics

arXiv:2604.21172v1 Announce Type: cross Abstract: This paper develops a refined version of TAPO-description logic for the analysis of information behavior. The framework is treated not as a single hom

Ternary Memristive Logic: Hardware for Reasoning Realized via Domain Algebra

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks

arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a

The Path Not Taken: Duality in Reasoning about Program Execution

arXiv:2604.20917v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of

Time, Causality, and Observability Failures in Distributed AI Inference Systems

arXiv:2604.21361v1 Announce Type: new Abstract: Distributed AI inference pipelines rely heavily on timestamp-based observability to understand system behavior. This work demonstrates that even small c

Transient Turn Injection: Exposing Stateless Multi-Turn Vulnerabilities in Large Language Models

arXiv:2604.21860v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This pape

Unbiased Prevalence Estimation with Multicalibrated LLMs

arXiv:2604.21549v1 Announce Type: new Abstract: Estimating the prevalence of a category in a population using imperfect measurement devices (diagnostic tests, classifiers, or large language models) is

UniGenDet: A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection

arXiv:2604.21904v1 Announce Type: new Abstract: In recent years, significant progress has been made in both image generation and generated image detection. Despite their rapid, yet largely independent

safetyarxiv-cs-cv

VistaBot: View-Robust Robot Manipulation via Spatiotemporal-Aware View Synthesis

model-releasesarxiv-cs-ro

arXiv:2604.21914v1 Announce Type: new Abstract: Recently, end-to-end robotic manipulation models have gained significant attention for their generalizability and scalability. However, they often suffe

Weighting What Matters: Boosting Sample Efficiency in Medical Report Generation via Token Reweighting

arXiv:2604.21082v1 Announce Type: new Abstract: Training vision-language models (VLMs) for medical report generation is often hindered by the scarcity of high-quality annotated data. This work evaluat

When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs

arXiv:2604.21911v1 Announce Type: cross Abstract: Despite impressive progress in capabilities of large vision-language models (LVLMs), these systems remain vulnerable to hallucinations, i.e., outputs

You Only Gaussian Once: Controllable 3D Gaussian Splatting for Ultra-Densely Sampled Scenes

arXiv:2604.21400v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has revolutionized neural rendering, yet existing methods remain predominantly research prototypes ill-suited for productio

A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images

arXiv:2507.07800v3 Announce Type: replace-cross Abstract: Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes. However, this task is high

researcharxiv-cs-cv

A Synchronized Audio-Visual Multi-View Capture System

arXiv:2603.23089v2 Announce Type: replace Abstract: Multi-view capture systems have been an important tool in research for recording human motion under controlling conditions. Most existing systems ar

safetyarxiv-cs-cv

ACT: Anti-Crosstalk Learning for Cross-Sectional Stock Ranking via Temporal Disentanglement and Structural Purification

arXiv:2604.20204v1 Announce Type: new Abstract: Cross-sectional stock ranking is a fundamental task in quantitative investment, relying on both temporal modeling of individual stocks and the capture o

researcharxiv-cs-lg

AgentLens: Adaptive Visual Modalities for Human-Agent Interaction in Mobile GUI Agents

arXiv:2604.20279v1 Announce Type: cross Abstract: Mobile GUI agents can automate smartphone tasks by interacting directly with app interfaces, but how they should communicate with users during executi

agentsarxiv-cs-ai

AnatomicalNets: A Multi-Structure Segmentation and Contour-Based Distance Estimation Pipeline for Clinically Grounded Lung Cancer T-Staging

arXiv:2511.19367v2 Announce Type: replace-cross Abstract: Accurate tumor staging in lung cancer is crucial for prognosis and treatment planning and is governed by explicit anatomical criteria under fi

Behavioral Transfer in AI Agents: Evidence and Privacy Implications

arXiv:2604.19925v1 Announce Type: cross Abstract: AI agents powered by large language models are increasingly acting on behalf of humans in social and economic environments. Prior research has focused

agentsarxiv-cs-ai

Believing without Seeing: Quality Scores for Contextualizing Vision-Language Model Explanations

arXiv:2509.25844v3 Announce Type: replace Abstract: When people query Vision-Language Models (VLMs) but cannot see the accompanying visual context (e.g. for blind and low-vision users), augmenting VLM