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arXiv:2604.24934v1 Announce Type: new Abstract: Intelligent Transportation Systems (ITS) increasingly rely on vision-based perception and learning-based control, necessitating experimental platforms t

agentsarxiv-cs-ro

Teacher Forcing as Generalized Bayes: Optimization Geometry Mismatch in Switching Surrogates for Chaotic Dynamics

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DGX agent

arXiv:2604.25904v1 Announce Type: new Abstract: Identity teacher forcing (ITF) enables stable training of deterministic recurrent surrogates for chaotic dynamical systems and has been highly effective

researcharxiv-cs-lg

29 Apr 2026

Hardware

Tendon-Actuated Robots with a Tapered, Flexible Polymer Backbone: Design, Fabrication, and Modeling

arXiv:2603.19124v2 Announce Type: replace Abstract: This paper presents the design, modeling, and fabrication of 3D-printed, tendon-actuated continuum robots featuring a flexible, tapered backbone con

hardwarearxiv-cs-ro

The Dynamics of Delusion: Modeling Bidirectional False Belief Amplification in Human-Chatbot Dialogue

arXiv:2604.25096v1 Announce Type: new Abstract: There is growing concern that AI chatbots might fuel delusional beliefs in users. Some have suggested that humans and chatbots mutually reinforce false

The Forensic Cost of Watermark Removal

model-releasesarxiv-cs-cv

arXiv:2604.25491v1 Announce Type: new Abstract: Current watermark removal methods are evaluated on two axes: attack success rate and perceptual quality. We show this is insufficient. While state-of-th

The Rashomon Effect for Visualizing High-Dimensional Data

arXiv:2604.00485v2 Announce Type: replace Abstract: Dimension reduction (DR) is inherently non-unique: multiple embeddings can preserve the structure of high-dimensional data equally well while differ

safetyarxiv-cs-lg

The Role of Symmetry in Optimizing Overparameterized Networks

arXiv:2604.25150v1 Announce Type: new Abstract: Overparameterization is central to the success of deep learning, yet the mechanisms by which it improves optimization remain incompletely understood. We

The Russian Legislative Corpus

arXiv:2406.04855v3 Announce Type: replace Abstract: We present a comprehensive corpus of Russian primary and secondary legislation adopted between 1991 and 2025, comprising 304,382 texts (194,425,905

The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models

arXiv:2604.25359v1 Announce Type: new Abstract: Large Language Models are increasingly being deployed to extract structured data from unstructured and semi-structured sources: parsing invoices, medica

The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic Segmentation

arXiv:2604.25530v1 Announce Type: new Abstract: Recent knowledge distillation (KD) methods for semantic segmentation introduce increasingly complex hand-crafted objectives, yet are typically evaluated

The Surprising Universality of LLM Outputs: A Real-Time Verification Primitive

arXiv:2604.25634v1 Announce Type: cross Abstract: We report a striking statistical regularity in frontier LLM outputs that enables a CPU-only scoring primitive running at 2.6 microseconds per token, w

The Thinking Pixel: Recursive Sparse Reasoning in Multimodal Diffusion Latents

model-releasesarxiv-cs-cv

arXiv:2604.25299v1 Announce Type: new Abstract: Diffusion models have achieved success in high-fidelity data synthesis, yet their capacity for more complex, structured reasoning like text following ta

Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models

arXiv:2510.16340v2 Announce Type: replace Abstract: Recent advances in post-training techniques have endowed Large Language Models (LLMs) with enhanced capabilities for tackling complex, logic-intensi

Agents

Threat-Oriented Digital Twinning for Security Evaluation of Autonomous Platforms

arXiv:2604.25757v1 Announce Type: cross Abstract: Open, unclassified research on secure autonomy is constrained by limited access to operational platforms, contested communications infrastructure, and

agentsarxiv-cs-ro

Three Models of RLHF Annotation: Extension, Evidence, and Authority

arXiv:2604.25895v1 Announce Type: cross Abstract: Preference-based alignment methods, most prominently Reinforcement Learning with Human Feedback (RLHF), use the judgments of human annotators to shape

Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning

arXiv:2604.24811v1 Announce Type: new Abstract: Graph neural Ordinary Differential Equations (ODE) combine neural ODE with the message passing mechanism of Graph Neural Networks (GNN), providing a con

TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

arXiv:2604.25545v1 Announce Type: new Abstract: Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical i

researcharxiv-cs-cv

TouchAI: Exploring human-AI perceptual alignment in touch through language model representations

arXiv:2406.06587v2 Announce Type: replace Abstract: Aligning large language models (LLMs) behaviour with human intent is critical for future AI. An important yet often overlooked aspect of this alignm

Toward a Functional Geometric Algebra for Natural Language Semantics

arXiv:2604.25902v1 Announce Type: new Abstract: Distributional and neural approaches to natural language semantics have been built almost exclusively on conventional linear algebra: vectors, matrices,

Toward Multimodal Conversational AI for Age-Related Macular Degeneration

arXiv:2604.25720v1 Announce Type: cross Abstract: Despite strong performance of deep learning models in retinal disease detection, most systems produce static predictions without clinical reasoning or

Towards interpretable AI with quantum annealing feature selection

arXiv:2604.25649v1 Announce Type: new Abstract: Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and

Towards Robust Deep Learning-based Rumex Obtusifolius Detection from Drone Images

arXiv:2604.25316v1 Announce Type: new Abstract: Domain adaptation (DA) addresses the challenge of transferring a machine learning model trained on a source domain to a target domain with a different d

researcharxiv-cs-cv

Towards Seamless Lunar Mosaics: Deep Radiometric Normalization for Cross-Sensor Orbital Imagery Using Chandrayaan-2 TMC Data

arXiv:2604.25208v1 Announce Type: new Abstract: Radiometric inconsistencies remain a major challenge in generating seamless lunar mosaics from multi-mission orbital imagery due to variability in illum

Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2604.25131v1 Announce Type: new Abstract: Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically requi

Transformer Approximations from ReLUs

arXiv:2604.24878v1 Announce Type: new Abstract: We provide a systematic recipe for translating ReLU approximation results to softmax attention mechanism. This recipe covers many common approximation t

TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2604.25898v1 Announce Type: new Abstract: Continual offline reinforcement learning (CORL) aims to learn a sequence of tasks from datasets collected over time while preserving performance on prev

Hardware

UltraGS: Real-Time Physically-Decoupled Gaussian Splatting for Ultrasound Novel View Synthesis

arXiv:2511.07743v3 Announce Type: replace Abstract: Ultrasound imaging is a cornerstone of non-invasive clinical diagnostics, yet its limited field of view poses challenges for novel view synthesis. W

hardwarearxiv-cs-cv

Uncovering Exotic Paired States in the 2D Spin-Imbalanced Fermi Gas with Neural Wave Functions

arXiv:2604.24883v1 Announce Type: cross Abstract: We study the zero-temperature phase diagram of the 2D spin-imbalanced Fermi gas with short-ranged attractive interactions using the recently developed

UniSER: A Foundation Model for Unified Soft Effects Removal

arXiv:2511.14183v3 Announce Type: replace Abstract: Digital images are often degraded by soft effects such as lens flare, haze, shadows, and reflections, which reduce aesthetics even though the underl

Unrequited Emotions: Investigating the Gaps in Motivation and Practice in Speech Emotion Recognition Research

arXiv:2604.25776v1 Announce Type: new Abstract: Critical analyses of emotion recognition technology have raised ethical concerns around task validity and potential downstream impacts, urging researche

Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health

arXiv:2410.09635v2 Announce Type: replace Abstract: Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, acc

Applications

VAE-Inf: A statistically interpretable generative paradigm for imbalanced classification

arXiv:2604.25334v1 Announce Type: new Abstract: Imbalanced classification remains a pervasive challenge in machine learning, particularly when minority samples are too scarce to provide a robust discr

applicationsarxiv-cs-lg

Variational approach to nonholonomic and inequality-constrained mechanics

arXiv:2409.11063v3 Announce Type: replace-cross Abstract: Variational principles play a central role in classical mechanics, providing compact formulations of dynamics and direct access to conserved q

researcharxiv-cs-ro

Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty

model-releasesarxiv-cs-lg

arXiv:2604.25897v1 Announce Type: cross Abstract: Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes

Applications

VibeToken: Scaling 1D Image Tokenizers and Autoregressive Models for Dynamic Resolution Generations

arXiv:2604.24885v1 Announce Type: new Abstract: We introduce an efficient, resolution-agnostic autoregressive (AR) image synthesis approach that generalizes to arbitrary resolutions and aspect ratios,

applicationsarxiv-cs-cv

ViPO: Visual Preference Optimization at Scale

arXiv:2604.24953v1 Announce Type: new Abstract: While preference optimization is crucial for improving visual generative models, how to effectively scale this paradigm remains largely unexplored. Curr

VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis

arXiv:2604.24894v1 Announce Type: cross Abstract: We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction gu

safetyarxiv-cs-cv

Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models

arXiv:2604.25570v1 Announce Type: new Abstract: Spiking Transformers have shown strong potential for long-range visual modeling through spike-driven self-attention. However, their quadratic token inte

researcharxiv-cs-cv

VLM Judges Can Rank but Cannot Score: Task-Dependent Uncertainty in Multimodal Evaluation

arXiv:2604.25235v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used as automated judges for multimodal systems, yet their scores provide no indication of reliability.

Vocabulary Dropout for Curriculum Diversity in LLM Co-Evolution

arXiv:2604.03472v2 Announce Type: replace Abstract: Co-evolutionary self-play, where one language model generates problems and another solves them, promises autonomous curriculum learning without huma

Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation

arXiv:2511.21517v2 Announce Type: replace Abstract: Unlike text, speech conveys information about the speaker, such as gender, through acoustic cues like pitch. This gives rise to modality-specific bi

VOYAGER: A Training Free Approach for Generating Diverse Datasets using LLMs

arXiv:2512.12072v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly being used to generate synthetic datasets for the evaluation and training of downstream models. Howeve

Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models

arXiv:2604.25591v1 Announce Type: cross Abstract: Recent audio-aware large language models (ALLMs) have demonstrated strong capabilities across diverse audio understanding and reasoning tasks, but the

What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective

arXiv:2604.25132v1 Announce Type: new Abstract: Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an

When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient

arXiv:2604.25872v1 Announce Type: new Abstract: Training language models via reinforcement learning often relies on imperfect proxy rewards, since ground truth rewards that precisely define the intend

safetyarxiv-cs-lg

When the Forger Is the Judge: GPT-Image-2 Cannot Recognize Its Own Faked Documents

model-releasesarxiv-cs-cv

arXiv:2604.25213v1 Announce Type: new Abstract: OpenAI's GPT-Image-2 has effectively erased the visual boundary between authentic and AI-edited document images: a single number on a receipt can be rep

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs

arXiv:2510.07499v2 Announce Type: replace Abstract: Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge

Hardware

WhisperPipe: A Resource-Efficient Streaming Architecture for Real-Time Automatic Speech Recognition

arXiv:2604.25611v1 Announce Type: new Abstract: Real-time automatic speech recognition (ASR) systems face a fundamental trade-off between transcription accuracy and computational efficiency, particula

hardwarearxiv-cs-cl