All entries

arXiv:2508.15840v5 Announce Type: replace-cross Abstract: When using a public communication channel--whether formal or informal, such as commenting or posting on social media--end users have no expect

agentsarxiv-cs-cl

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Using ASP(Q) to Handle Inconsistent Prioritized Data

DGX agent

arXiv:2604.21603v1 Announce Type: cross Abstract: We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data

researcharxiv-cs-ai

24 Apr 2026

Using Machine Mental Imagery for Representing Common Ground in Situated Dialogue

arXiv:2604.21144v1 Announce Type: cross Abstract: Situated dialogue requires speakers to maintain a reliable representation of shared context rather than reasoning only over isolated utterances. Curre

Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi

researcharxiv-cs-lg

Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models

arXiv:2604.20995v1 Announce Type: new Abstract: Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning

VARestorer: One-Step VAR Distillation for Real-World Image Super-Resolution

arXiv:2604.21450v1 Announce Type: cross Abstract: Recent advancements in visual autoregressive models (VAR) have demonstrated their effectiveness in image generation, highlighting their potential for

Verifying Machine Learning Interpretability Requirements through Provenance

arXiv:2604.21599v1 Announce Type: cross Abstract: Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software e

researcharxiv-cs-lg

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models

arXiv:2510.18457v3 Announce Type: replace Abstract: The performance of Latent Diffusion Models (LDMs) is critically dependent on the quality of their visual tokenizers. While recent works have explore

safetyarxiv-cs-cv

VFM^{4}SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection

arXiv:2604.21502v1 Announce Type: new Abstract: In real-world scenarios, continual changes in weather, illumination, and imaging conditions cause significant domain shifts, leading detectors trained o

safetyarxiv-cs-cv

VG-CoT: Towards Trustworthy Visual Reasoning via Grounded Chain-of-Thought

arXiv:2604.21396v1 Announce Type: cross Abstract: The advancement of Large Vision-Language Models (LVLMs) requires precise local region-based reasoning that faithfully grounds the model's logic in act

VidHal: Benchmarking Temporal Hallucinations in Vision LLMs

arXiv:2411.16771v3 Announce Type: replace Abstract: Vision Large Language Models (VLLMs) are widely acknowledged to be prone to hallucinations. Existing research addressing this problem has primarily

Vista4D: Video Reshooting with 4D Point Clouds

arXiv:2604.21915v1 Announce Type: new Abstract: We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically,

applicationsarxiv-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

VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models

arXiv:2604.03956v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models are emerging as embodied foundation models for robotic manipulation, but their deployment introduces a new

VLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation

arXiv:2604.21375v1 Announce Type: cross Abstract: Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without verifiable evidence, and repet

VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping

arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm

researcharxiv-cs-ai

Watts-per-Intelligence Part II: Algorithmic Catalysis

arXiv:2604.20897v1 Announce Type: cross Abstract: We develop a thermodynamic theory of algorithmic catalysis within the watts-per-intelligence framework, identifying reusable computational structures

researcharxiv-cs-ai

Weighted quantization using MMD: From mean field to mean shift via gradient flows

arXiv:2502.10600v4 Announce Type: replace-cross Abstract: Approximating a probability distribution using a set of particles is a fundamental problem in machine learning and statistics, with applicatio

researcharxiv-cs-lg

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

researcharxiv-cs-cl

WFM: 3D Wavelet Flow Matching for Ultrafast Multi-Modal MRI Synthesis

arXiv:2604.21146v1 Announce Type: new Abstract: Diffusion models have achieved remarkable quality in multi-modal MRI synthesis, but their computational cost (hundreds of sampling steps and separate mo

When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors

model-releasesarxiv-cs-cl

arXiv:2604.21255v1 Announce Type: new Abstract: Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents sh

When Bigger Isn't Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisation

arXiv:2604.21309v1 Announce Type: new Abstract: Multi-document news summarisation systems are increasingly adopted for their convenience in processing vast daily news content, making fairness across d

safetyarxiv-cs-cl

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

When to Trust the Answer: Question-Aligned Semantic Nearest Neighbor Entropy for Safer Surgical VQA

arXiv:2511.01458v2 Announce Type: replace-cross Abstract: Safety and reliability are critical for deploying visual question answering (VQA) systems in surgery, where incorrect or ambiguous responses c

Who Defines 'Best'? Towards Interactive, User-Defined Evaluation of LLM Leaderboards

arXiv:2604.21769v1 Announce Type: new Abstract: LLM leaderboards are widely used to compare models and guide deployment decisions. However, leaderboard rankings are shaped by evaluation priorities set

Who Defines Fairness? Target-Based Prompting for Demographic Representation in Generative Models

arXiv:2604.21036v1 Announce Type: new Abstract: Text-to-image(T2I) models like Stable Diffusion and DALL-E have made generative AI widely accessible, yet recent studies reveal that these systems often

Why are all LLMs Obsessed with Japanese Culture? On the Hidden Cultural and Regional Biases of LLMs

arXiv:2604.21751v1 Announce Type: cross Abstract: LLMs have been showing limitations when it comes to cultural coverage and competence, and in some cases show regional biases such as amplifying Wester

Why Do Language Model Agents Whistleblow?

arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds

WildSplatter: Feed-forward 3D Gaussian Splatting with Appearance Control from Unconstrained Images

arXiv:2604.21182v1 Announce Type: new Abstract: We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting

applicationsarxiv-cs-cv

Wiring the 'Why': A Unified Taxonomy and Survey of Abductive Reasoning in LLMs

arXiv:2604.08016v2 Announce Type: replace Abstract: Regardless of its foundational role in human discovery and sense-making, abductive reasoning--the inference of the most plausible explanation for an

Words that make SENSE: Sensorimotor Norms in Learned Lexical Token Representations

arXiv:2602.00469v2 Announce Type: replace-cross Abstract: While word embeddings derive meaning from co-occurrence patterns, human language understanding is grounded in sensory and motor experience. We

researcharxiv-cs-ai

WorldMark: A Unified Benchmark Suite for Interactive Video World Models

arXiv:2604.21686v1 Announce Type: new Abstract: Interactive video generation models such as Genie, YUME, HY-World, and Matrix-Game are advancing rapidly, yet every model is evaluated on its own benchm

X2-N: A Transformable Wheel-legged Humanoid Robot with Dual-mode Locomotion and Manipulation

arXiv:2604.21541v1 Announce Type: new Abstract: Wheel-legged robots combine the efficiency of wheeled locomotion with the versatility of legged systems, enabling rapid traversal over both continuous a

applicationsarxiv-cs-ro

XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration

arXiv:2505.11336v4 Announce Type: replace Abstract: Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality sci

safetyarxiv-cs-cl

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

Zero-Shot Detection of LLM-Generated Text via Implicit Reward Model

arXiv:2604.21223v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across various tasks. However, their ability to generate human-like text has ra

ZipFold: Modular Actuators for Scaleable Adaptive Robots

arXiv:2604.05260v2 Announce Type: replace Abstract: There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However,

researcharxiv-cs-ro

3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models

arXiv:2604.05687v2 Announce Type: replace Abstract: Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-de

researcharxiv-cs-cv

A Computational Model of Message Sensation Value in Short Video Multimodal Features that Predicts Sensory and Behavioral Engagement

arXiv:2604.19995v1 Announce Type: new Abstract: The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal featur

researcharxiv-cs-cv

Hardware

A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing

arXiv:2604.20129v1 Announce Type: new Abstract: The Synergistic Collapse occurs when scaling beyond 100 agents causes superlinear performance degradation that individual optimizations cannot prevent.

hardwarearxiv-cs-lg

Agents

A Field Guide to Decision Making

arXiv:2604.20669v1 Announce Type: cross Abstract: High-consequence decision making demands peak performance from individuals in positions of responsibility. Such executive authority bears the obligati

agentsarxiv-cs-ai

Agents

A Hierarchical MARL-Based Approach for Coordinated Retail P2P Trading and Wholesale Market Participation of DERs

arXiv:2604.20586v1 Announce Type: new Abstract: The ongoing shift towards decentralization of the electric energy sector, driven by the growing electrification across end-use sectors, and widespread a

agentsarxiv-cs-lg

A Hough transform approach to safety-aware scalar field mapping using Gaussian Processes

arXiv:2604.20799v1 Announce Type: new Abstract: This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe

safetyarxiv-cs-ro

A Kinematic Framework for Evaluating Pinch Configurations in Robotic Hand Design without Object or Contact Models

arXiv:2604.20692v1 Announce Type: new Abstract: Evaluating the pinch capability of a robotic hand is important for understanding its functional dexterity. However, many existing grasp evaluation metho

researcharxiv-cs-ro

A Multi-Plant Machine Learning Framework for Emission Prediction, Forecasting, and Control in Cement Manufacturing

arXiv:2604.19903v1 Announce Type: cross Abstract: Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, s

applicationsarxiv-cs-ai

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 Survey of Scaling in Large Language Model Reasoning

arXiv:2504.02181v2 Announce Type: replace Abstract: The rapid advancements in large Language models (LLMs) have significantly enhanced their reasoning capabilities, driven by various strategies such a

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