Search: “models”

FreeOcc: Training-Free Embodied Open-Vocabulary Occupancy Prediction

arXiv:2604.28115v1 Announce Type: cross Abstract: Existing learning-based occupancy prediction methods rely on large-scale 3D annotations and generalize poorly across environments. We present FreeOcc,

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Function-based Parametric Co-Design Optimization of Dexterous Hands

DGX agent

arXiv:2604.27557v1 Announce Type: new Abstract: Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting system

model-releasesarxiv-cs-ro

1 May 2026

GAVEL: Towards Rule-Based Safety Through Activation Monitoring

arXiv:2601.19768v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly paired with activation-based monitoring to detect and prevent harmful behaviors that may not be appare

safetyarxiv-cs-ai

Global Optimality for Constrained Exploration via Penalty Regularization

model-releasesarxiv-cs-lg

arXiv:2604.28144v1 Announce Type: new Abstract: Efficient exploration is a central problem in reinforcement learning and is often formalized as maximizing the entropy of the state-action occupancy mea

GuideDog: A Real-World Egocentric Multimodal Dataset for Blind and Low-Vision Accessibility-Aware Guidance

arXiv:2503.12844v2 Announce Type: replace Abstract: For people affected by blindness and low vision (BLV), safe and independent navigation remains a major challenge, impacting over 2.2 billion individ

HQ-UNet: A Hybrid Quantum-Classical U-Net with a Quantum Bottleneck for Remote Sensing Image Segmentation

arXiv:2604.27206v1 Announce Type: new Abstract: Semantic segmentation in remote sensing is commonly addressed using classical deep learning architectures such as U-Net, which require a large number of

Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks

arXiv:2505.13230v3 Announce Type: replace Abstract: Scaling laws in deep learning -- empirical power-law relationships linking model performance to resource growth -- have emerged as simple yet striki

safetyarxiv-cs-lg

Improving Graph Few-shot Learning with Hyperbolic Space and Denoising Diffusion

arXiv:2604.27462v1 Announce Type: cross Abstract: Graph few-shot learning, which focuses on effectively learning from only a small number of labeled nodes to quickly adapt to new tasks, has garnered s

Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering

arXiv:2604.27724v1 Announce Type: new Abstract: Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual c

JI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification

arXiv:2604.27343v1 Announce Type: new Abstract: Skin lesion classification is essential for early dermatological diagnosis, yet many existing computer-aided systems rely primarily on dermoscopic image

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs 'Difficult' Downstream Tasks in LLMs

arXiv:2310.02277v4 Announce Type: replace-cross Abstract: We present Junk DNA Hypothesis by adopting a novel task-centric angle for the pre-trained weights of large language models (LLMs). It has been

researcharxiv-cs-ai

Learning Generalizable Multimodal Representations for Software Vulnerability Detection

arXiv:2604.25711v2 Announce Type: replace-cross Abstract: Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capt

Learning to Aggregate Zero-Shot LLM Agents for Corporate Disclosure Classification

arXiv:2603.20965v2 Announce Type: replace-cross Abstract: This paper studies whether a lightweight supervised aggregator can combine diverse zero-shot large language model outputs into a stronger down

researcharxiv-cs-ai

Leveraging Quantum-Based Architectures for Robust Diagnostics

arXiv:2511.12386v2 Announce Type: replace Abstract: Quantum machine learning has emerged as a promising approach for medical image analysis, particularly in settings where compact models and expressiv

researcharxiv-cs-cv

LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic Reasoning

arXiv:2604.27960v1 Announce Type: new Abstract: Recent large language models (LLMs) have achieved impressive reasoning milestones but continue to struggle with high computational costs, logical incons

researcharxiv-cs-ai

LLMs Capture Emotion Labels, Not Emotion Uncertainty: Distributional Analysis and Calibration of Human--LLM Judgment Gaps

arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i

researcharxiv-cs-cl

Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs

arXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma

Mind the Gap: Structure-Aware Consistency in Preference Learning

arXiv:2604.27733v1 Announce Type: new Abstract: Preference learning has become the foundation of aligning Large Language Models (LLMs) with human intent. Popular methods, such as Direct Preference Opt

safetyarxiv-cs-lg

MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs

model-releasesarxiv-cs-cl

arXiv:2504.02768v4 Announce Type: replace Abstract: We introduce MultiBLiMP 1.0, a massively multilingual benchmark of linguistic minimal pairs, covering 101 languages and 2 types of subject-verb agre

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

model-releasesarxiv-cs-lg

arXiv:2510.18183v2 Announce Type: replace Abstract: Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains

arXiv:2604.27852v1 Announce Type: cross Abstract: Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retri

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

Local Ai

OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving

arXiv:2512.14044v3 Announce Type: replace-cross Abstract: The deployment of Vision-Language Models (VLMs) in safety-critical domains like autonomous driving (AD) is critically hindered by reliability

local-aiarxiv-cs-ai

Applications

Probabilistic Circuits for Irregular Multivariate Time Series Forecasting

arXiv:2604.27814v1 Announce Type: new Abstract: Joint probabilistic modeling is essential for forecasting irregular multivariate time series (IMTS) to accurately quantify uncertainty. Existing approac

applicationsarxiv-cs-lg

RoadMapper: A Multi-Agent System for Roadmap Generation of Solving Complex Research Problems

model-releasesarxiv-cs-cl

arXiv:2604.27616v1 Announce Type: new Abstract: People commonly leverage structured content to accelerate knowledge acquisition and research problem solving. Among these, roadmaps guide researchers th

Applications

Robust Learning on Heterogeneous Graphs with Heterophily: A Graph Structure Learning Approach

arXiv:2604.27387v1 Announce Type: new Abstract: Heterogeneous graphs with heterophily have emerged as a powerful abstraction for modeling complex real-world systems, where nodes of different types and

applicationsarxiv-cs-ai

Agents

SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation

arXiv:2604.27620v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unsee

agentsarxiv-cs-cv

Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception

arXiv:2604.28048v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as proxies for human perception in urban analysis, yet it remains unclear whether persona prompting p

safetyarxiv-cs-cl

Hardware

Strait: Perceiving Priority and Interference in ML Inference Serving

arXiv:2604.28175v1 Announce Type: new Abstract: Machine learning (ML) inference serving systems host deep neural network (DNN) models and schedule incoming inference requests across deployed GPUs. How

hardwarearxiv-cs-lg

Student Classroom Behavior Recognition Based on Improved YOLOv8s

arXiv:2604.27293v1 Announce Type: new Abstract: In classroom teaching, student behavior can reflect their learning state and classroom participation, which is of great significance for teaching qualit

researcharxiv-cs-cv

Local Ai

TeD-Loc: Text Distillation for Weakly Supervised Object Localization

arXiv:2501.12632v2 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spat

local-aiarxiv-cs-cv

The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms

arXiv:2604.27274v1 Announce Type: new Abstract: As AI transitions toward multi-agent systems (MAS) to solve complex workflows, research paradigms operate on the axiomatic assumption that agent collabo

To Diff or Not to Diff? Structure-Aware and Adaptive Output Formats for Efficient LLM-based Code Editing

arXiv:2604.27296v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code editing, yet the prevalent full-code generation paradigm suffers from severe efficiency bo

researcharxiv-cs-cl

TransVLM: A Vision-Language Framework and Benchmark for Detecting Any Shot Transitions

arXiv:2604.27975v1 Announce Type: cross Abstract: Traditional Shot Boundary Detection (SBD) inherently struggles with complex transitions by formulating the task around isolated cut points, frequently

Validating the Clinical Utility of CineECG 3D Reconstructions through Cross-Modal Feature Attribution

arXiv:2604.27017v1 Announce Type: cross Abstract: Deep learning models for 12-lead electrocardiogram (ECG) analysis achieve high diagnostic performance but lack the intuitive interpretability required

researcharxiv-cs-lg

VTBench: A Multimodal Framework for Time-Series Classification with Chart-Based Representations

arXiv:2604.27259v1 Announce Type: new Abstract: Time-series classification (TSC) has advanced significantly with deep learning, yet most models rely solely on raw numerical inputs, overlooking alterna

researcharxiv-cs-cv

WindowsWorld: A Process-Centric Benchmark of Autonomous GUI Agents in Professional Cross-Application Environments

arXiv:2604.27776v1 Announce Type: new Abstract: While GUI agents have shown impressive capabilities in common computer-use tasks such as OSWorld, current benchmarks mainly focus on isolated and single

Hardware

ZipCCL: Efficient Lossless Data Compression of Communication Collectives for Accelerating LLM Training

arXiv:2604.27844v1 Announce Type: cross Abstract: Communication has emerged as a critical bottleneck in the distributed training of large language models (LLMs). While numerous approaches have been pr

hardwarearxiv-cs-cl

3D-LENS: A 3D Lifting-based Elevated Novel-view Synthesis method for Single-View Aerial-Ground Re-Identification

arXiv:2604.26520v1 Announce Type: new Abstract: Aerial-Ground Re-Identification (AG-ReID) is constrained by the viewpoint-domain gap, as drastic viewpoint disparities occlude or distort discriminative

A Multistage Extraction Pipeline for Long Scanned Financial Documents: An Empirical Study in Industrial KYC Workflows

arXiv:2604.26462v1 Announce Type: new Abstract: Structured information extraction from long, multilingual scanned financial documents is a core requirement in industrial KYC and compliance workflows.

A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework

arXiv:2604.25933v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which

safetyarxiv-cs-ai

Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding

arXiv:2604.26779v1 Announce Type: cross Abstract: RL post-training of frontier language models is increasingly bottlenecked by autoregressive rollout generation, making rollout acceleration a central

safetyarxiv-cs-cl

Adaptive and Fine-grained Module-wise Expert Pruning for Efficient LoRA-MoE Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2604.26340v1 Announce Type: new Abstract: LoRA-MoE has emerged as an effective paradigm for parameter-efficient fine-tuning, combining the low training cost of LoRA with the increased adaptation

AirZoo: A Unified Large-Scale Dataset for Grounding Aerial Geometric 3D Vision

arXiv:2604.26567v1 Announce Type: new Abstract: Despite the rapid progress in data-driven 3D vision, aerial geometric 3D vision remains a formidable challenge due to the severe scarcity of large-scale

Beyond Shortcuts: Mitigating Visual Illusions in Frozen VLMs via Qualitative Reasoning

arXiv:2604.26250v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) have achieved state-of-the-art performance in general visual tasks, their perceptual robustness remains remarkably b

safetyarxiv-cs-cv

Applications

CheXthought: A global multimodal dataset of clinical chain-of-thought reasoning and visual attention for chest X-ray interpretation

arXiv:2604.26288v1 Announce Type: cross Abstract: Chest X-ray interpretation is one of the most frequently performed diagnostic tasks in medicine and a primary target for AI development, yet current v

applicationsarxiv-cs-ai

ChinaTravel: An Open-Ended Travel Planning Benchmark with Compositional Constraint Validation for Language Agents

arXiv:2412.13682v5 Announce Type: replace Abstract: Travel planning stands out among real-world applications of Language Agents because it couples significant practical demand with a rigorous constrai

ClawGym: A Scalable Framework for Building Effective Claw Agents

arXiv:2604.26904v1 Announce Type: cross Abstract: Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around th