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Thermal-Only Crowd Counting with Deployment-Time Privacy Protection

arXiv:2605.17042v1 Announce Type: new Abstract: While RGB-Thermal crowd counting has shown promise, the paradigm faces critical limitations: RGB data raises privacy concerns in public surveillance, an

applicationsarxiv-cs-cv

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Local Ai

Thinking with Patterns: Breaking the Perceptual Bottleneck in Visual Planning via Pattern Induction

DGX agent

arXiv:2605.16848v1 Announce Type: cross Abstract: Planning from raw visual input remains a significant challenge for current Vision-Language Models (VLMs), when the complexity of input is beyond their

local-aiarxiv-cs-ai

19 May 2026

Threats to Arabic Handwriting Recognition: Investigating Black-Box Adversarial Attacks on embedded ConvNet models

model-releasesarxiv-cs-cv

arXiv:2605.18058v1 Announce Type: new Abstract: Arabic handwriting recognition (AHR) has made significant progress with deep learning models. AHR research has largely focused on performance, with secu

Throughput-Optimal Scheduling Algorithms for LLM Inference and AI Agents

arXiv:2504.07347v3 Announce Type: replace-cross Abstract: As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While

agentsarxiv-cs-lg

TIER: Trajectory-Invariant Execution Rewards for Multi-Step Tool Composition

arXiv:2605.16790v1 Announce Type: cross Abstract: Tool use enables large language models to solve complex tasks through sequences of API calls, yet existing reinforcement learning approaches fail to s

Hardware

TierCheck: Tiered Checkpointing for Fault Tolerance in Large Language Model Training

arXiv:2605.17821v1 Announce Type: cross Abstract: Large Language Model (LLM) training is frequently interrupted by a heterogeneous spectrum of failures, from common GPU crashes to catastrophic cluster

hardwarearxiv-cs-ai

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval

model-releasesarxiv-cs-cv

arXiv:2605.18434v1 Announce Type: cross Abstract: E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This im

Time-Efficient Hybrid Hyperparameter Tuning Approach for Cardiovascular Disease Classification

arXiv:2411.18234v2 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are any serious illness of the heart, which require accurate diagnosis to prevent fatal consequences. Hyperpara

Time Series Foundation Models as Strong Baselines in Transportation Forecasting: A Large-Scale Benchmark Analysis

model-releasesarxiv-cs-lg

arXiv:2602.24238v2 Announce Type: replace Abstract: Accurate forecasting of transportation dynamics is essential for urban mobility and infrastructure planning. Although recent work has achieved stron

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model

arXiv:2605.18013v1 Announce Type: cross Abstract: Segment Anything Model 2 (SAM 2) serves as a core foundation model in the field of video segmentation. Building upon the original SAM model, it introd

To MRL or not to MRL: Text Embeddings are Robust to Truncation Without Matryoshka Embeddings, Except In Heavy Truncation Scenarios

arXiv:2605.16608v1 Announce Type: cross Abstract: Matryoshka Representation Learning (MRL) is a widely adopted approach for training text encoders so they provide useful text representations at variou

researcharxiv-cs-cl

To Trust or Not to Trust: Authors' Response to AI-based Reviews

arXiv:2605.16623v1 Announce Type: cross Abstract: Large language models are increasingly discussed and used as tools that may assist with scholarly peer review, but empirical evidence regarding how au

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate

Hardware

Token-Space Mask Prediction for Efficient Vision Transformer Segmentation

arXiv:2605.18177v1 Announce Type: new Abstract: Query-based Vision Transformer segmentation models typically reconstruct dense spatial feature maps to predict masks, inheriting design patterns from co

hardwarearxiv-cs-cv

Tongyi DeepResearch Technical Report

arXiv:2510.24701v3 Announce Type: replace-cross Abstract: We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking res

ToolMATH: A Diagnostic Benchmark for Long-Horizon Tool Use under Systematic Tool-Catalog Constraints

model-releasesarxiv-cs-cl

arXiv:2602.21265v2 Announce Type: replace Abstract: We introduce ToolMATH, a math-grounded diagnostic benchmark for evaluating long-horizon tool use under controllable tool-catalog conditions. ToolMAT

Topo-GS: Continuous Volumetric Embedding of High-Dimensional Data via Topological Gaussian Splatting

arXiv:2605.17011v1 Announce Type: cross Abstract: Dimensionality reduction algorithms map high-dimensional data into visualizable 2D or 3D spaces, but traditionally rely on a discrete point-cloud para

researcharxiv-cs-cv

Topological Data Analysis combined with Machine Learning for Predicting Permeability of Porous Media

arXiv:2605.17581v1 Announce Type: cross Abstract: Flow in porous media is difficult to address using standard analytical or numerical methods due to its complexity. However, since synthetic representa

TouchMap-OR: Multi-View 3D Mapping of Hand-Surface Contacts

arXiv:2605.17638v1 Announce Type: new Abstract: Hand-surface interactions between clinicians, patients, and medical equipment play a central role in pathogen transmission during medical procedures. Ho

researcharxiv-cs-cv

Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM

arXiv:2605.17217v1 Announce Type: cross Abstract: Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) prov

Toward Robust Multilingual Adaptation of LLMs for Low-Resource Languages

arXiv:2510.14466v3 Announce Type: replace-cross Abstract: Large language models (LLMs) continue to struggle with low-resource languages, primarily due to limited training data, translation noise, and

safetyarxiv-cs-ai

Toward Template-Free Explainability for Monte Carlo Tree Search

arXiv:2605.16524v1 Announce Type: cross Abstract: Probabilistic search algorithms, such as Monte Carlo Tree Search (MCTS), have proven very effective in solving sequential decision-making tasks under

Local Ai

Towards Generalized Image Manipulation Localization via Score-based Model

arXiv:2605.16879v1 Announce Type: new Abstract: With the rapid evolution of synthetic media, Image Manipulation Localization (IML) has emerged as a critical component in multimedia forensics for ensur

local-aiarxiv-cs-cv

Towards Human-Level Book-Writing Capability

arXiv:2605.17064v1 Announce Type: new Abstract: Large language models optimized for instruction following and agentic tasks remain poorly aligned with the requirements of high-quality creative writing

Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning

model-releasesarxiv-cs-ro

arXiv:2602.10503v2 Announce Type: replace Abstract: Pretrained on large-scale and diverse datasets, VLA models demonstrate strong generalization and adaptability as general-purpose robotic policies. H

Towards Migrating Neural Network Implementations

arXiv:2511.02610v2 Announce Type: replace Abstract: The development of smart systems (i.e., systems enhanced with AI components) has thrived thanks to the rapid advancements in neural networks (NNs).

Towards Principled Test-Time Adaptation for Time Series Forecasting

arXiv:2605.17250v1 Announce Type: new Abstract: Test-time adaptation (TTA) has recently emerged as a promising approach for improving time series forecasting (TSF) under distribution shift. Existing T

Towards Robust Argumentative Essay Understanding via TIDE: An Interactive Framework with Trial and Debate

arXiv:2605.17247v1 Announce Type: new Abstract: Argumentative essays serve as a vital medium for assessing critical thinking and reasoning skills, yet there is limited works on accurately understandin

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

arXiv:2605.17994v1 Announce Type: cross Abstract: New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize pres

safetyarxiv-cs-ai

Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments

arXiv:2605.18385v1 Announce Type: cross Abstract: We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-

Towards Universal Physical Adversarial Attacks via a Joint Multi-Objective and Multi-Model Optimization Framework

arXiv:2605.17772v1 Announce Type: new Abstract: Physical adversarial attacks often overfit single surrogate models and optimization objectives. While ensemble attacks can mitigate this, existing metho

safetyarxiv-cs-cv

Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space

arXiv:2605.17704v1 Announce Type: new Abstract: The lottery ticket hypothesis posits that dense networks contain sparse subnetworks, ``winning tickets,'' that, when rewound to their initial weights an

Tutorials

TPGDiff: Hierarchical Triple-Prior Guided Diffusion for Image Restoration

arXiv:2601.20306v2 Announce Type: replace Abstract: All-in-one image restoration aims to address diverse degradation types using a single unified model. Existing methods typically rely on degradation

tutorialsarxiv-cs-cv

TPV: Parameter Perturbations Through the Lens of Test Prediction Variance

model-releasesarxiv-cs-lg

arXiv:2512.11089v4 Announce Type: replace-cross Abstract: We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifyin

Local Ai

TRACE: Evidence Grounding-Guided Multi-Video Event Understanding and Claim Generation

arXiv:2605.16740v1 Announce Type: new Abstract: Multi-video event understanding demands models that can locate and attribute query-relevant evidence scattered across long, heterogeneous video corpora.

local-aiarxiv-cs-cv

TRACE: Trajectory Correction from Cross-layer Evidence for Hallucination Reduction

arXiv:2605.18163v1 Announce Type: new Abstract: Hallucination correction is not a one-direction problem. We show that intermediate layers are neither uniformly more truthful than final layers nor unif

Traces of Social Competence in Large Language Models

arXiv:2603.04161v2 Announce Type: replace Abstract: The False Belief Test (FBT) has been the main method for assessing Theory of Mind (ToM) and related socio-cognitive competencies. For Large Language

applicationsarxiv-cs-cl

Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning

arXiv:2601.19624v2 Announce Type: replace-cross Abstract: Real-world reinforcement learning often faces environment drift, but most existing methods rely on static entropy coefficients/target entropy,

applicationsarxiv-cs-ai

Train the Trainers -- An Agentic AI Framework for Peer-Based Mental Health Support in Battlefield Environments

arXiv:2605.16269v1 Announce Type: cross Abstract: Modern military operations expose soldiers to sustained psychological stress, leading to acute reactions, post-traumatic stress symptoms, and other me

Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew

arXiv:2605.17938v1 Announce Type: cross Abstract: Training data attribution (TDA) should enable generative model interpretability and foster a variety of related downstream tasks. Nonetheless, current

applicationsarxiv-cs-ai

Local Ai

Training-Free Occluded Text Rendering via Glyph Priors and Attention-Guided Semantic Blending

arXiv:2605.16810v1 Announce Type: new Abstract: We present a training-free framework for occluded text rendering with a pretrained FLUX.1-dev backbone. The task requires a model to render recognizable

local-aiarxiv-cs-cv

Training Infinitely Deep and Wide Transformers

arXiv:2605.17660v1 Announce Type: cross Abstract: Transformers have become the dominant architecture in modern machine learning, yet the theoretical understanding of their training dynamics remains li

Trajectory-Aware Adaptive Inference in Object Detection Models

arXiv:2605.16397v1 Announce Type: cross Abstract: The increasing integration of sensors in autonomous maritime navigation has led to large-scale multimodal datasets, raising challenges in achieving ef

Transfer Learning for Customized Car Racing Environments

arXiv:2605.17928v1 Announce Type: cross Abstract: Transfer Learning, a technique where a model/agent can use the knowledge/expertise that it gained from one task and exploit that to solve another clos

agentsarxiv-cs-lg

Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)

arXiv:2605.16735v1 Announce Type: cross Abstract: The deployment of 5G Multicast-Broadcast Services (MBS) is emerging as a critical technology for spectral-efficient UHD content delivery and serving a

safetyarxiv-cs-lg

Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights

arXiv:2505.03205v3 Announce Type: replace Abstract: Transformers serve as the foundational architecture for large language and video generation models, such as GPT, BERT, SORA and their successors. Em

applicationsarxiv-cs-lg

Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment

arXiv:2605.17342v1 Announce Type: cross Abstract: Standard RLHF relies on transitive scalar rewards, failing to capture the cyclic nature of human preferences. While some approaches like the General P

TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT

model-releasesarxiv-cs-cv

arXiv:2605.16572v1 Announce Type: new Abstract: Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly i