Search: “models”

Mind the Cap: Output-Budget Regimes Change the Measured Multilingual Reasoning Gap

model-releasesarxiv-cs-cl

arXiv:2608.04160v1 Announce Type: new Abstract: Multilingual evaluations report accuracy at a single output-token cap, but languages need different numbers of tokens to express the same content, so th

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MoCA: Multi-modal Cross-masked Autoencoder for Digital Health Measurements

DGX agent

arXiv:2506.02260v4 Announce Type: replace-cross Abstract: Wearable devices enable continuous multi-modal physiological and behavioral monitoring, yet analysis of these data streams faces fundamental c

model-releasesarxiv-cs-lg

6 Aug 2026

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Flow-matching

arXiv:2608.05103v1 Announce Type: new Abstract: Data assimilation (DA) uses Bayesian inference to update the state of a numerical forecast model with observed data. In this study, we propose a fundame

Non-asymptotic implicit bias of logistic regression at early-stage gradient descent dynamics

model-releasesarxiv-cs-lg

arXiv:2608.04382v1 Announce Type: new Abstract: Gradient descent has been of particular interest in modern machine learning beyond sole focus on optimization. Implicit bias emerging from optimization,

Not All Redundant Tokens Are Alike: Analyzing Visual Token Pruning through Token Roles

arXiv:2608.04483v1 Announce Type: new Abstract: Vision-language models (VLMs) process an image as a sequence of visual tokens, which creates a substantial computational bottleneck during inference. Re

safetyarxiv-cs-cv

Applications

Objects as Audio-Visual Modal Sound Fields

arXiv:2608.05145v1 Announce Type: new Abstract: While modern 3D reconstruction excels at modeling object geometry and appearance, it largely ignores the rich acoustic cues revealed through physical in

applicationsarxiv-cs-cv

OPD-V: Visual On-Policy Self-Distillation with Modality Balance

arXiv:2608.05131v1 Announce Type: cross Abstract: On-Policy Self-Distillation (OPSD) has become a standard post-training approach for improving visual reasoning in multimodal large language models (ML

safetyarxiv-cs-ai

Optimizing What Policies Learn From: Recoverability-aware Rollout Intervention Learning

arXiv:2608.05080v1 Announce Type: cross Abstract: Critic-free group-based reinforcement learning has become a scalable approach for post-training large language models. However, most existing methods

safetyarxiv-cs-cl

PADFormer: Pose-agnostic Anomaly Detection from Sparse View Images

arXiv:2608.04210v1 Announce Type: new Abstract: Pose-agnostic Anomaly Detection (PAD) remains challenging as anomalies can appear under arbitrary viewpoints, requiring methods to handle significant po

Patients-like-me: A Variational LM--GNN Framework for Explainable Clinical Prediction

arXiv:2608.04193v1 Announce Type: cross Abstract: Language models (LMs) offer strong textual representations for electronic health records (EHRs), but they encode patient sequences in isolation and pr

Perception Before Reasoning: Dynamic Latent Reasoning for Video Understanding and Question Answering

arXiv:2608.04124v1 Announce Type: cross Abstract: Video question answering requires models to ground language queries in visual evidence and, when necessary, reason over that evidence across time. Exi

PriDyG: Privacy-preserving Dynamic Graph Inference with LLM-GNN Collaboration

arXiv:2608.04255v1 Announce Type: cross Abstract: Graph inference over relational data can expose sensitive edge information, and this risk becomes more severe in dynamic graphs, where repeated model

Prototype-based Self-Supervised Multimodal Learning for PPG and Accelerometry Signals

arXiv:2510.09764v2 Announce Type: replace Abstract: Modeling multi-modal time-series data is critical for capturing system-level dynamics, particularly in biosignals where modalities such as ECG, PPG,

Relational Response Fields: A General Theory of Black-Box LLM Response Consistency and Recovery

arXiv:2608.04552v1 Announce Type: new Abstract: Black-box language-model reliability is commonly pursued by sampling, prompting, voting, verifying, or iteratively revising individual answers. We ask a

researcharxiv-cs-cl

RepairFormer: Automated Repair of Structured Inputs Using Transformers

arXiv:2608.05060v1 Announce Type: cross Abstract: Structured input files such as JSON, DOT, OBJ, INI, S-expression, and TinyC are widely used in software systems, but small corruptions can cause parse

ResPlan: A Large-Scale Vector-Graph Dataset of 17,000 Residential Floor Plans

arXiv:2508.14006v2 Announce Type: replace Abstract: We introduce ResPlan, a dataset of 17,000 residential floor plans with vector geometry, room-connectivity graphs, and metric-scale coordinates. Each

Rethinking Pixel Mean Flows via Interval Denoiser

arXiv:2608.04818v1 Announce Type: new Abstract: Modern diffusion and flow-based models are increasingly moving toward few-step, latent-free generation to bypass the computational overhead of multi-ste

RiboSphere: Learning Unified and Efficient Representations of RNA Structures

arXiv:2603.19636v2 Announce Type: replace Abstract: Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimen

RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning

arXiv:2601.05451v2 Announce Type: replace-cross Abstract: Recent advances in text-to-SQL have been driven by larger models, better datasets, and new training methods like RLVR. However, progress remai

researcharxiv-cs-cl

RUTA: Principled Visual Token Allocation via Rate-Utility Optimization

arXiv:2608.04132v1 Announce Type: new Abstract: High-resolution images and long videos provide vision-language models with rich context for multimodal reasoning and fine-grained perception, but the re

Tutorials

Spatiotemporal Graph Transformer for Traffic Intelligence in Edge Computing

arXiv:2608.04075v1 Announce Type: cross Abstract: Accurate traffic forecasting is essential for proactive resource management in edge computing, where service demand evolves dynamically across both sp

tutorialsarxiv-cs-ai

Stabilizing Multi-Attack Adversarial Training via Bandit Optimization

arXiv:2511.12265v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) remain vulnerable to diverse adversarial perturbations, motivating multi-attack adversarial training (AT) for impr

Suppression Sticks, Locality Is Fragile: A Closed-Loop Target-and-Control Audit of Task-Vector Negation in VLA Policies

arXiv:2608.04692v1 Announce Type: cross Abstract: Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We presen

Talk2Sensors: 3D Visual Grounding in Autonomous Driving via Sensor-Adaptive Physical Cue Matching

arXiv:2608.04568v1 Announce Type: new Abstract: As a key capability for embodied intelligence, 3D visual grounding (3DVG) has been predominantly studied in indoor scenes with RGB-D or point-cloud inpu

The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations

arXiv:2608.05050v1 Announce Type: cross Abstract: Against the backdrop of violence in police interactions with the U.S. public, we explore how deferentially police officers speak to virtual characters

researcharxiv-cs-ai

The Evaluator Is Part of the Experiment: Measuring Open-Ended LLM Conformity

model-releasesarxiv-cs-cl

arXiv:2608.04463v1 Announce Type: new Abstract: Prior work on LLM conformity largely measures discrete answer flips under verifiable labels. Open-ended revisions require a different measurement strate

The Neural Echo: A Signal Processing Perspective for Understanding Neural Networks

arXiv:2608.04864v1 Announce Type: cross Abstract: We introduce the neural echo as a tool for understanding the behavior of neural networks. It generalizes the model-based concepts of impulse responses

Tutorials

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis

tutorialsarxiv-cs-ai

Toward Integrating Adaptive Experience Replay and Online Uncertainty Estimation in Safe Actor-Critic Optimal Control

arXiv:2608.04732v1 Announce Type: cross Abstract: Safe actor-critic control often treats barrier filtering, uncertainty estimation, and experience replay as separate modules, even though each changes

Towards Trustworthy Hypergraph Neural Networks under Label Noise

arXiv:2608.04377v1 Announce Type: cross Abstract: Hypergraph neural networks (HGNNs) have demonstrated remarkable capabilities in processing complex higher-order relationships. However, their performa

Training Crossroads for Recurrent Vision Transformers: Recurrence, Neural ODEs, and Deep Supervision

arXiv:2608.04879v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong image-recognition performance, but their parameter count grows linearly with depth when each block is indepe

Training-Free Hashing-Based Attention via Binary Principal Components

arXiv:2608.04405v1 Announce Type: cross Abstract: Long-context large language models (LLMs) are increasingly deployed in real-world applications, yet self-attention remains a major efficiency bottlene

TRCoRSurg: Temporal-Relational Co-Reasoning for Surgical Video Triplet Recognition

arXiv:2608.04606v1 Announce Type: new Abstract: Understanding complex surgical scenes requires recognizing multiple interdependent entities, such as instruments, actions, and targets, while maintainin

TriCLE: Tri-Modal Vision-Language Reasoning for Edge-Deployed Fine-Grained Clustering

arXiv:2608.04175v1 Announce Type: new Abstract: Edge platforms used for aerial observation must interpret aircraft imagery under limited memory, limited compute, and intermittent connectivity. This se

safetyarxiv-cs-cv

Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)

arXiv:2608.04317v1 Announce Type: cross Abstract: Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost

Variational Bounds for Perceptron Learning from Structured Data

arXiv:2608.04882v1 Announce Type: new Abstract: We introduce a variational approach to a finite-temperature continuous-spin perceptron trained on a Gaussian mixture. The model allows for a broad class

When Does Latent Communication Pay? A Causal Audit of Relayed KV Caches in Multi-Agent LLMs

arXiv:2608.04893v1 Announce Type: cross Abstract: Multi-agent LLM systems relay key--value caches instead of text and credit their gains to exchanged ``latent thoughts''. That credit is a claim about

Why Ranking Anomaly Detection Algorithms Isn't as Reliable as You May Think

model-releasesarxiv-cs-lg

arXiv:2608.04613v1 Announce Type: new Abstract: Anomaly detection is a safety-critical machine learning problem with applications ranging from fraud detection to network intrusion prevention and indus

Agents

ZoomV: Temporal Zoom-in for Efficient Long Video Understanding

arXiv:2504.01407v3 Announce Type: replace-cross Abstract: Long video understanding poses a fundamental challenge for large video-language models (LVLMs) due to the overwhelming number of frames and th

agentsarxiv-cs-ai

A Graph Signal Processing Perspective on Numerical Sequence Representations in LLM In-Context Learning

arXiv:2608.03015v1 Announce Type: cross Abstract: Pretrained large language models (LLMs) have demonstrated in-context learning (ICL) capabilities for numerical inference over sequences serialized as

A Physics-Informed Hybrid Neural Operator for Transient Magnetization Prediction in Power Magnetics

arXiv:2608.02965v1 Announce Type: new Abstract: Magnetic components in high-frequency, high-power-density converters are increasingly driven by non-sinusoidal flux-density waveforms with fast transiti

A Unified Resolution-Conditioned Framework for Orthogonal Line-Scanning Image Fusion

arXiv:2608.03107v1 Announce Type: new Abstract: Laser line-scanning microscopy enables fast volumetric imaging but produces anisotropic lateral resolution. Orthogonal line scans provide complementary

AgenticECO: An Agentic Framework for ECO on 3D Integrated Circuits

arXiv:2608.03738v1 Announce Type: new Abstract: As Moore's law slows, the industry is turning to three-dimensional integration; yet in merged 3D-IC flows, routed designs expose bond-level defects with

AI Agent Economics: Can Autonomous Economic Behavior Emerge among AI Agents under Minimal External Conditions?

arXiv:2608.03076v1 Announce Type: new Abstract: Multi-agent studies commonly place AI agents in predefined games, markets, or roles, making it difficult to distinguish endogenous economic organization

Agents

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution

arXiv:2608.01366v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are integral to complex intellectual tasks, yet output quality remains constrained by user-provided prompts. Iter

agentsarxiv-cs-ai

Beyond Solving: Prescriptive Probing for Neural Routing Solvers

arXiv:2602.07216v2 Announce Type: replace Abstract: Neural combinatorial optimization (NCO) trains fast heuristics for routing problems, but planners often need more than a single solve: they ask whic

Beyond the Gegenbauer Paradigm: q-Orthogonal Kernels for Machine Learning

model-releasesarxiv-cs-lg

arXiv:2608.03482v1 Announce Type: new Abstract: The performance of Support Vector Machines (SVMs) critically depends on the kernel function choice, which enables implicit mapping of data into high-dim

Bi-Lipschitz Ansatz for Anti-Symmetric Functions

arXiv:2503.04263v2 Announce Type: replace Abstract: Motivated by applications to the simulation of quantum many-body systems by neural networks, researchers have suggested several models which are ant