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TomaMMU: A Comprehensive Multimodal Understanding Benchmark for Tomato Leaf Diseases

arXiv:2608.08727v1 Announce Type: cross Abstract: To address this gap, we introduce TomaMMU, a large-scale Tomato leaf disease MultiModal Understanding dataset, alongside TomaBench, a benchmark for ev

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TongGuOCR: A Layout-Aware and Token-Augmented OCR Framework for Chinese Historical Documents

DGX agent

arXiv:2608.07917v1 Announce Type: new Abstract: Chinese historical documents preserve valuable cultural heritage, but many collections remain accessible only as scanned page images, preventing full-te

model-releasesarxiv-cs-ai

11 Aug 2026

Tools to Explain Neural Networks for Power System Dynamics

arXiv:2608.08048v1 Announce Type: cross Abstract: This paper presents, for the first time in power systems literature to our knowledge, analytical tools to explain the training performance of machine

ToolUniverse: An open platform for democratizing AI scientists

arXiv:2509.23426v3 Announce Type: replace Abstract: AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because

Agents

ToolVision: Learning When and How to Use Visual Tools with Capability-Aligned Supervision

arXiv:2608.08907v1 Announce Type: cross Abstract: Thinking with images allows a multimodal model to compensate for limited perception by invoking visual tools through code. Yet the prevailing SFT-then

agentsarxiv-cs-ai

Topographic Constraints Shape Brain-Like Component Structure in Auditory Models

arXiv:2509.24039v2 Announce Type: replace-cross Abstract: If topography is a fundamental feature of the brain, it should influence both how neurons are arranged in space (i.e. explain brain maps) and

Topology-Aware Global-Local Mamba Networks for Palm Vein Biometrics

model-releasesarxiv-cs-cv

arXiv:2608.08951v1 Announce Type: new Abstract: Palm-vein recognition is a fine-grained biometric task in which both local vascular texture and the global layout of the vessel tree carry discriminativ

Toward CT-Equivalent Image Quality in Low-Dose Radiotherapy Planning: Conditional Diffusion-Based CBCT-to-CT Synthesis and the Impact of CBCT Input Representation

arXiv:2608.08919v1 Announce Type: cross Abstract: During standard radiotherapy planning, repeated CT acquisitions are often required for patient registration, verification, and adaptive planning, resu

Toward Mask Annotation-Free Surgical Instrument Segmentation from Endoscopic Images Using Text-Prompted Segment Anything Model 3 (SAM3)

model-releasesarxiv-cs-cv

arXiv:2608.08844v1 Announce Type: new Abstract: Surgical instrument segmentation is a fundamental task for computer-assisted interventions, yet most existing methods rely on pixel-level annotations or

Toward Metacognitive One-Shot Indirect Prompt Injection: Strategy Abstraction Via Outcome-Conditioned Reflection

model-releasesarxiv-cs-cl

arXiv:2608.08795v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents are vulnerable to indirect prompt injection (IPI), in which malicious instructions embedded in external o

Applications

Towards Adaptive Super-Resolution and Quality Assessment via Test-Time Adaptation

arXiv:2608.08508v1 Announce Type: new Abstract: This paper presents doctoral research on adaptive video super-resolution and perceptual quality modeling under real-world conditions. Existing video sup

applicationsarxiv-cs-cv

Towards an Argumentative Foundation for Evaluative AI

arXiv:2608.07473v1 Announce Type: new Abstract: Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting co

Towards an LLM-based method for quantifying the sexual content in song lyrics

model-releasesarxiv-cs-cl

arXiv:2608.08885v1 Announce Type: cross Abstract: Reggaeton is one of the most widely consumed music genres in the world, and its lyrics are commonly regarded as highly sexualized. This claim rests mo

Agents

Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives

arXiv:2608.09541v1 Announce Type: new Abstract: Connected Autonomous Vehicles (CAVs) increasingly exploit Vehicle-to-Everything (V2X) communication to exchange multi-source sensor information, enablin

agentsarxiv-cs-cv

Towards Expert-level Medical AI for Real-time Video Consultations

arXiv:2608.09861v1 Announce Type: new Abstract: Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness through

Towards Expressive and Faithful Audio-to-Image Generation: A Unified Multimodal Dataset and Synthesis Framework

arXiv:2608.09529v1 Announce Type: new Abstract: As an important subfield of cross-modal generation, synthesizing static visual content in the form of images from audio, namely audio-to-image (A2I) gen

safetyarxiv-cs-cv

Towards Realistic Guarantees: A Probabilistic Certificate for SmoothLLM

arXiv:2511.18721v4 Announce Type: replace-cross Abstract: The SmoothLLM defense provides a certification guarantee against jailbreaking attacks, but it relies on a strict 'k-unstable' assumption that

Towards Researcher Agents for Knowledge-Graph Question Answering

arXiv:2608.07700v1 Announce Type: new Abstract: Translating a natural-language question into a SPARQL query that can be executed against a large knowledge graph requires resolving lexical ambiguity, g

Toy project: a chat title model that fits in 5 MiB of ram

model-releasesr-localllama

Not even sure if I'm allowed to post this, what with the 'completely/primarily LLM generated copy' rule (the post itself is fine, but the repo/model I'm sharing definitely is, whoops) and the whole li

TRACE-Memory: Public-Conditioned Retrieval and Utility-Aware Evidence Admission for Personalized Generation

arXiv:2608.08446v1 Announce Type: new Abstract: Personalized generation systems retrieve user history by request--memory relevance and inject it into the model context. Yet relevant history may concer

TRACE: TRajectory Attribution for Automated Context Engineering

arXiv:2608.09153v1 Announce Type: new Abstract: Production AI agents fail when their context sources -- system prompts, knowledge bases, tool descriptions, and procedural skills -- contain errors or g

Applications

Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators

arXiv:2608.07630v1 Announce Type: new Abstract: We adapt two classical statistical estimators for quantifying uncertainty to modern deep learning, in order to provide clearer insights into uncertainty

applicationsarxiv-cs-lg

Tracking the Best Strategy in an Extensive-Form Game

model-releasesarxiv-cs-lg

arXiv:2608.09501v1 Announce Type: new Abstract: We consider the extensive-form bandit problem where on each trial the learner plays an extensive-form game against an oblivious adversary. We focus on t

Training-Free Universal Approximation by Prompting Random Transformers

arXiv:2608.09558v1 Announce Type: new Abstract: How expressive is prompting a transformer? Answering this question is important for separating the roles of prompting, architecture, and pretraining in

Training Variable Long Sequences with Data-Centric Parallel

arXiv:2608.07524v1 Announce Type: new Abstract: Training deep learning models on variable long sequences poses significant computational challenges. Existing methods force a difficult trade-off betwee

Trajectory Design and Budgeted Querying for Digital Twin Calibration

model-releasesarxiv-cs-lg

arXiv:2608.08631v1 Announce Type: new Abstract: Digital-twin calibration requires interaction data that is expensive to collect. We study two acquisition decisions: which trajectories to generate, and

Trajectory Divergence Horizon Decision for Reliable Dual-Arm Surgical Subtask Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.09125v1 Announce Type: new Abstract: Surgical robotic systems are increasingly being adopted as clinical workload rises, motivating autonomous solutions for repetitive manipulation subtasks

Trajectory-Induced Self-Calibration for Hidden-Target Localization Through an Unknown-Pose Range-Bearing Relay

arXiv:2608.09464v1 Announce Type: cross Abstract: This paper studies hidden-target localization from range-bearing packets reported by a relay beacon whose global position and yaw are unknown. The veh

researcharxiv-cs-ro

Transfer Learning-Enabled Distortion Compensation for Amplitude-Phase-Time Block Modulation-Based Nonlinear Single-Carrier Wireless Communications

arXiv:2608.08554v1 Announce Type: cross Abstract: Power amplifier (PA) nonlinearity and memory effects significantly limit the spectral compliance, reliability, and energy efficiency of communication

Transformer-Based Neural Quantum Digital Twins for Many-Body Spectral Reconstruction and Adaptive Quantum-Annealing Schedule Design

arXiv:2505.15662v3 Announce Type: replace-cross Abstract: We introduce Transformer-based Neural Quantum Digital Twins (Tx-NQDTs) to reconstruct the low-energy spectral evolution of many-body quantum s

Tutorials

Transformer Circuits Can Realize Clustering Algorithms

arXiv:2506.19125v2 Announce Type: replace-cross Abstract: Although transformers are most commonly optimized as statistical sequence models, it is unclear to what extent they can implement and learn ex

tutorialsarxiv-cs-ai

Tutorials

Transformer Explainer: Learning LLM Transformers with Interactive Visual Explanation and Experimentation

arXiv:2408.04619v2 Announce Type: replace-cross Abstract: The Transformer architecture underpins modern large language models powering state-of-the-art text generation and AI applications. However, it

tutorialsarxiv-cs-ai

Transformers for Multimodal Brain State Decoding: Integrating Functional Magnetic Resonance Imaging Data and Medical Metadata

arXiv:2512.08462v2 Announce Type: replace Abstract: Decoding brain states from functional magnetic resonance imaging (fMRI) data is vital for advancing neuroscience and clinical applications. While tr

Local Ai

TransNRank: Towards Accurate Neoantigen Ranking with Transformer

arXiv:2608.01924v2 Announce Type: replace-cross Abstract: Personalized neoantigen prediction is challenging due to the scarcity of positive samples, the noise of the experimental data, the severe clas

local-aiarxiv-cs-ai

TREAT: Evaluating Access to Formal Knowledge across Equivalent Mathematical Representations

arXiv:2608.07540v1 Announce Type: new Abstract: AI systems increasingly operate between flexible input representations and formal objects used by downstream tools. A key challenge is recognizing when

Tree-of-Experience: Hierarchical Experience Management for Self-Evolving Agents

arXiv:2608.09044v1 Announce Type: new Abstract: Continual self-evolution requires LLM agents to transform environmental interactions into reliable and reusable experience. Existing methods typically r

researcharxiv-cs-cl

TreeHop: Efficient Embedding-Level Query Rewriter

arXiv:2504.20114v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems face significant challenges in multi-hop question answering (MHQA), where complex queries require

Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation

arXiv:2608.09052v1 Announce Type: cross Abstract: Semi-supervised adaptation of vision foundation models (VFMs) commonly freezes the pretrained backbone and updates lightweight modules such as LoRA. H

TriView-YOLO: Early Multi-View Fusion for Ground Penetrating Radar Cavity Detection in Soft, High-Water-Content Soils

arXiv:2608.09522v1 Announce Type: new Abstract: Automated detection of subsurface cavities from Ground Penetrating Radar (GPR) is most difficult in soft, high-water-content ground, where conductive, w

researcharxiv-cs-cv

Tropical Cyclone Forecasting via Latent Rectified Flow using Satellite Imagery and Atmospheric Fields

arXiv:2608.08354v1 Announce Type: new Abstract: Tropical cyclones are growing more destructive in a changing climate, and efficient forecasting of their structure and track has become a necessity. Dee

researcharxiv-cs-cv

TrustRoboReward: Preference-Ordered Isotonic Score Editing for Multi-Paradigm Robot Reward Models

arXiv:2608.08491v1 Announce Type: new Abstract: Reward models are a bottleneck for reinforcement learning in embodied AI. Long-horizon robotic manipulation requires scalable vision feedback beyond han

Tutorials

TS-Mob: Social and Geographical-Aware Time Series Foundation-Model Framework for Human Mobility Prediction

arXiv:2507.00945v2 Announce Type: replace Abstract: Short-term forecasting of aggregated human mobility flows supports urban planning, intelligent transportation systems, and emergency response, yet e

tutorialsarxiv-cs-lg

TSDS-Toolbox: A Toolbox for Measuring Time-Series Dataset Similarity

arXiv:2608.08119v1 Announce Type: new Abstract: The rapid advancement of artificial intelligence (AI) has significantly accelerated research in time-series analysis, particularly in forecasting, class

TSPORec: Token Selection via Preference Optimization for LLM-Based Sequential Recommendation

arXiv:2608.09605v1 Announce Type: cross Abstract: Large Language Models (LLMs) have emerged as powerful tools for improving recommendation systems. The effectiveness of LLMs arises from their ability

Twin Rollouts: Noise-Coupled Counterfactual Branching in Interactive Video World Models

arXiv:2608.08982v1 Announce Type: new Abstract: Interactive video world models generate rollouts autoregressively under an action stream, yet they are trained and evaluated almost exclusively on factu

Two-Layer Linear Auto-Regressive Models Estimate Latent States

arXiv:2606.12691v2 Announce Type: replace-cross Abstract: Auto-regressive models have emerged as powerful tools for sequential data, from language to video. Understanding how and why these models lear

Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields

arXiv:2608.09071v1 Announce Type: cross Abstract: Forward uncertainty propagation in complex physical systems can induce structured covariance across field-valued outputs. For a probabilistic surrogat

Ultra-Low-Impedance Robotic Gripper for High-Bandwidth and Transparent Physical Interaction

arXiv:2608.09198v1 Announce Type: new Abstract: Conventional robotic grippers often use high-ratio transmissions to generate grasping torque and external force sensors to measure physical interaction.

researcharxiv-cs-ro