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arXiv:2604.24832v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) have recently emerged as a promising alternative to standard autoregressive large language models (AR-LLMs), yet

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Model Releases

One Perturbation, Two Failure Modes: Probing VLM Safety via Embedding-Guided Typographic Perturbations

DGX agent

arXiv:2604.25102v1 Announce Type: new Abstract: Typographic prompt injection exploits vision language models' (VLMs) ability to read text rendered in images, posing a growing threat as VLMs power auto

model-releasesarxiv-cs-cv

29 Apr 2026

One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement

arXiv:2604.25444v1 Announce Type: new Abstract: Large Language Models (LLMs) often fail to utilize their latent reasoning capabilities due to a distributional mismatch between ambiguous human inquirie

safetyarxiv-cs-cl

OneThinker: All-in-one Reasoning Model for Image and Video

arXiv:2512.03043v3 Announce Type: replace Abstract: Reinforcement learning (RL) has recently achieved remarkable success in eliciting visual reasoning within Multimodal Large Language Models (MLLMs).

Online combinatorial optimization with stochastic decision sets and adversarial losses

arXiv:2604.25269v1 Announce Type: new Abstract: Most work on sequential learning assumes a fixed set of actions that are available all the time. However, in practice, actions can consist of picking su

Online learning with Erdos-Renyi side-observation graphs

arXiv:2604.25271v1 Announce Type: cross Abstract: We consider adversarial multi-armed bandit problems where the learner is allowed to observe losses of a number of arms beside the arm that it actually

Optimal UGV-UAV Cooperative Partitioning and Inspection of Shortest Paths

arXiv:2604.25284v1 Announce Type: new Abstract: We study cooperative shortest path planning for an unmanned ground vehicle (UGV) assisted by an unmanned aerial vehicle (UAV) in environments with unkno

researcharxiv-cs-ro

Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians

arXiv:2604.25295v1 Announce Type: new Abstract: Continuous causal discovery typically couples representation learning with structural optimization via non-convex acyclicity penalties, which subjects s

Origin-Destination Demand Prediction: An Urban Radiation and Attraction Perspective

arXiv:2412.00167v2 Announce Type: replace Abstract: In recent years, origin-destination (OD) demand prediction has gained significant attention for its profound implications in urban development. Exis

Personalization Toolkit: Training Free Personalization of Large Vision Language Models

arXiv:2502.02452v4 Announce Type: replace Abstract: Personalization of Large Vision-Language Models (LVLMs) involves customizing models to recognize specific users or object instances and to generate

Tutorials

Personalized Cross-Modal Emotional Correlation Learning for Speech-Preserving Facial Expression Manipulation

arXiv:2604.25255v1 Announce Type: new Abstract: Speech-preserving facial expression manipulation (SPFEM) aims to enhance human expressiveness without altering mouth movements tied to the original spee

tutorialsarxiv-cs-cv

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space

arXiv:2604.05030v2 Announce Type: replace Abstract: Experiments probing natural language processing by both humans and LLMs suggest that the meaning of a semantic expression is indeterminate prior to

PhyloSDF: Phylogenetically-Conditioned Neural Generation of 3D Skull Morphology via Residual Flow Matching

arXiv:2604.25371v1 Announce Type: cross Abstract: Generating novel, biologically plausible three-dimensional morphological structures is a fundamental challenge in computational evolutionary biology,

Local Ai

Physics-Guided Tiny-Mamba Transformer for Reliability-Aware Early Fault Warning

arXiv:2601.21293v2 Announce Type: replace Abstract: Reliability-centered prognostics for rotating machinery requires early-warning signals that remain accurate under nonstationary operating conditions

local-aiarxiv-cs-lg

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters

arXiv:2602.17697v2 Announce Type: replace Abstract: Large Language Models (LLMs) are being increasingly used across a wide range of tasks. However, their substantial computational demands raise concer

PINNs in More General Geometry

arXiv:2604.25020v1 Announce Type: cross Abstract: Neural architectures trained with losses inspired by differential conditions are the basis for PINN models. Since many constructions in differential g

PLMGH: What Matters in PLM-GNN Hybrids for Code Classification and Vulnerability Detection

arXiv:2604.25599v1 Announce Type: cross Abstract: Code understanding models increasingly rely on pretrained language models (PLMs) and graph neural networks (GNNs), which capture complementary semanti

Policy Improvement Reinforcement Learning

arXiv:2604.00860v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a central post-training paradigm for improving the reasoning capabilities of large

safetyarxiv-cs-lg

PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference

arXiv:2604.24971v1 Announce Type: cross Abstract: We present PolyKV, a system in which multiple concurrent inference agents share a single, asymmetrically compressed KV cache pool. Rather than allocat

PortraVec: Image-Based Portrait Vectorization with Text-Guided Manipulation

arXiv:2410.04182v2 Announce Type: replace Abstract: While portrait sketch generation is a special task in sketch synthesis, most existing methods are pixel-based, limiting their interpretability and e

Power Foam: Unifying Real-Time Differentiable Ray Tracing and Rasterization

arXiv:2604.24994v1 Announce Type: cross Abstract: We introduce a differentiable 3D representation that unifies the ray tracing capabilities of foam-based ray tracing with the efficiency of modern rast

Hardware

Practical exposure correction via compensation

arXiv:2212.14245v2 Announce Type: replace Abstract: In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightnes

hardwarearxiv-cs-cv

Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost

arXiv:2604.25441v1 Announce Type: cross Abstract: Commercial TTS systems produce near-native Indic audio, but the best open-source bases (Chatterbox, Indic Parler-TTS, IndicF5) trail them on measured

Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models

arXiv:2604.25642v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual-textual understanding, yet their reliability is critically undermined b

Principled Detection of Hallucinations in Large Language Models via Multiple Testing

arXiv:2508.18473v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have emerged as powerful foundational models to solve a variety of tasks, they have also been shown to be prone t

researcharxiv-cs-cl

Prior-Aligned Data Cleaning for Tabular Foundation Models

arXiv:2604.25154v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) achieve state-of-the-art zero-shot accuracy on small tabular datasets by meta-learning over synthetic data-generating p

Privileged Foresight Distillation: Zero-Cost Future Correction for World Action Models

arXiv:2604.25859v1 Announce Type: new Abstract: World action models jointly predict future video and action during training, raising an open question about what role the future-prediction branch actua

researcharxiv-cs-ro

ProDrive: Proactive Planning for Autonomous Driving via Ego-Environment Co-Evolution

arXiv:2604.25329v1 Announce Type: new Abstract: End-to-end autonomous driving planners typically generate trajectories from current observations alone. However, real-world driving is highly dynamic, a

safetyarxiv-cs-ro

Progressing beyond Art Masterpieces or Touristic Cliches: how to assess your LLMs for cultural alignment?

arXiv:2604.25654v1 Announce Type: new Abstract: Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- unt

safetyarxiv-cs-cl

Tutorials

Provable Accelerated Bayesian Optimization with Knowledge Transfer

arXiv:2511.03125v2 Announce Type: replace-cross Abstract: We study how to accelerate Bayesian optimization (BO) on a target task by transferring historical knowledge from related source tasks. Existin

tutorialsarxiv-cs-lg

PSI-Bench: Towards Clinically Grounded and Interpretable Evaluation of Depression Patient Simulators

arXiv:2604.25840v1 Announce Type: new Abstract: Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulati

PSP: An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech

arXiv:2604.25476v1 Announce Type: cross Abstract: Standard text-to-speech (TTS) evaluation measures intelligibility (WER, CER) and overall naturalness (MOS, UTMOS) but does not quantify accent. A synt

QB-LIF: Learnable-Scale Quantized Burst Neurons for Efficient SNNs

arXiv:2604.25688v1 Announce Type: new Abstract: Binary spike coding enables sparse and event-driven computation in spiking neural networks (SNNs), yet its 1-bit-per-timestep representation fundamental

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

arXiv:2604.25884v1 Announce Type: cross Abstract: Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representatio

QFlash: Bridging Quantization and Memory Efficiency in Vision Transformer Attention

arXiv:2604.25306v1 Announce Type: new Abstract: FlashAttention improves efficiency through tiling, but its online softmax still relies on floating-point arithmetic for numerical stability, making full

Quantifying and Mitigating Socially Desirable Responding in LLMs: A Desirability-Matched Graded Forced-Choice Psychometric Study

arXiv:2602.17262v2 Announce Type: replace Abstract: Human self-report questionnaires are increasingly used in NLP to benchmark and audit large language models (LLMs), from persona consistency to safet

Quantum Dynamics via Score Matching on Bohmian Trajectories

arXiv:2604.25137v1 Announce Type: cross Abstract: We solve the time-dependent Schrodinger equation by learning the score function, the gradient of the log-probability density, on Bohmian trajectories.

Quantum-Inspired Robust and Scalable SAR Object Classification

arXiv:2604.25755v1 Announce Type: cross Abstract: SAR image classification naturally has to deal with huge noise and a high dynamic range particularly requiring robust classification models. Additiona

Query-Efficient Quantum Approximate Optimization via Graph-Conditioned Trust Regions

arXiv:2604.24803v1 Announce Type: new Abstract: In low-depth implementations of the Quantum Approximate Optimization Algorithm (QAOA), the dominant cost is often the number of objective evaluations ra

Agents

R^3-SQL: Ranking Reward and Resampling for Text-to-SQL

arXiv:2604.25325v1 Announce Type: cross Abstract: Modern Text-to-SQL systems generate multiple candidate SQL queries and rank them to judge a final prediction. However, existing methods face two limit

agentsarxiv-cs-cl

Local Ai

RABC-Net: Reliability-Aware Annotation-Free Skin Lesion Segmentation for Low-Resource Dermoscopy

arXiv:2604.05594v2 Announce Type: replace Abstract: Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combi

local-aiarxiv-cs-cv

Rapid tracking through strongly scattering media with physics-informed neuromorphic speckle analysis

arXiv:2604.25310v1 Announce Type: new Abstract: This work addresses the critical problem of tracking fast-moving objects through strongly scattering media in a low-light environment. Different from ex

RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation

arXiv:2603.09723v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used across the scientific workflow, including to draft peer-review reports. However, many AI-generate

RCProb: Probabilistic Rule Extraction for Efficient Simplification of Tree Ensembles

arXiv:2604.25304v1 Announce Type: new Abstract: Tree ensembles are widely used in industrial machine learning due to their strong predictive performance and efficient training procedures. However, as

Agents

Recursive Multi-Agent Systems

arXiv:2604.25917v1 Announce Type: cross Abstract: Recursive or looped language models have recently emerged as a new scaling axis by iteratively refining the same model computation over latent states

agentsarxiv-cs-cl

Reference-Augmented Learning for Precise Tracking Policy of Tendon-Driven Continuum Robots

arXiv:2604.25698v1 Announce Type: new Abstract: Tendon-Driven Continuum Robots (TDCRs) pose significant control challenges due to their highly nonlinear, path-dependent dynamics and non-Markovian char

safetyarxiv-cs-ro

Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models

arXiv:2604.25636v1 Announce Type: new Abstract: Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified ca

safetyarxiv-cs-cv

Reinforcement Learning for Testing Interdependent Requirements in Autonomous Vehicles: An Empirical Study

arXiv:2502.15792v2 Announce Type: replace-cross Abstract: Autonomous vehicles (AVs) make driving decisions without humans, making dependability assurance critical. Scenario-based testing is widely use

safetyarxiv-cs-lg