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TimeLesSeg: Unified Contrast-Agnostic Cross-Sectional and Longitudinal MS Lesion Segmentation via a Stochastic Generative Model

arXiv:2605.07955v1 Announce Type: cross Abstract: Multiple sclerosis (MS) expresses substantial clinical and radiological heterogeneity, which poses significant challenges for automatic lesion segment

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Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models

DGX agent

arXiv:2605.06683v1 Announce Type: cross Abstract: Transformer-based large language models are in some respects limited by the quadratic time and space computational complexity of attention. We introdu

model-releasesarxiv-cs-ai

11 May 2026

Tool Calling is Linearly Readable and Steerable in Language Models

arXiv:2605.07990v1 Announce Type: cross Abstract: When a tool-calling agent picks the wrong tool, the failure is invisible until execution: the email gets sent, the meeting gets missed. Probing 12 ins

Tools as Continuous Flow for Evolving Agentic Reasoning

arXiv:2605.07339v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in orchestrating tools for reasoning tasks. However, existing methods rely on a s

Topic Is Not Agenda: A Citation-Community Audit of Text Embeddings

model-releasesarxiv-cs-cl

arXiv:2605.07158v1 Announce Type: cross Abstract: Vector search and retrieval-augmented generation (RAG) rest on the assumption that cosine similarity between text embeddings reflects conceptual relat

Topology-Enhanced Alignment for Large Language Models: Trajectory Topology Loss and Topological Preference Optimization

arXiv:2605.07172v1 Announce Type: new Abstract: Alignment of large language models (LLMs) via SFT and RLHF/DPO typically ignores the global geometry of the representation space, relying instead on loc

local-aiarxiv-cs-cl

TopoPrune: Robust Data Pruning via Unified Latent Space Topology

arXiv:2602.02739v2 Announce Type: replace-cross Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geom

Toward Better Geometric Representations for Molecule Generative Models

arXiv:2605.07693v1 Announce Type: new Abstract: Geometric representation-conditioned molecule generation provides an effective paradigm that decouples molecule representation modeling from structure g

safetyarxiv-cs-lg

Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning

arXiv:2605.07799v1 Announce Type: cross Abstract: Training foundation models is computationally intensive and often slow to converge.We introduce PIQL,Privileged Information for Quick and Quality Lear

Towards an Inferentialist Account of Information Through Proof-theoretic Semantics

arXiv:2605.05368v2 Announce Type: replace-cross Abstract: Information is one of the most widely-discussed concepts of the current era. However, a great deal of insightful work notwithstanding, it is y

Applications

Towards Apples to Apples for AI Evaluations: From Real-World Use Cases to Evaluation Scenarios

arXiv:2605.07986v1 Announce Type: cross Abstract: AI measurement science has a wide variety of methodologies and measurements for comparing AI systems, resulting in what often appear to be 'apples-to-

applicationsarxiv-cs-ai

Agents

Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent

arXiv:2605.07202v1 Announce Type: new Abstract: Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limi

agentsarxiv-cs-ai

Hardware

Towards Billion-scale Multi-modal Biometric Search

arXiv:2605.07655v1 Announce Type: cross Abstract: Searching a multi-biometric database of a billion records for a country-level identity system requires pushing the limits of all aspects of a biometri

hardwarearxiv-cs-ai

Towards Closing the Autoregressive Gap in Language Modeling via Entropy-Gated Continuous Bitstream Diffusion

model-releasesarxiv-cs-cl

arXiv:2605.07013v1 Announce Type: new Abstract: Diffusion language models (DLMs) promise parallel, order-agnostic generation, but on standard benchmarks they have historically lagged behind autoregres

Towards Differentially Private Reinforcement Learning with General Function Approximation

arXiv:2605.07049v1 Announce Type: cross Abstract: We present the first theoretical guarantees for differentially private online reinforcement learning (RL) with general function approximation, extendi

safetyarxiv-cs-ai

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning

arXiv:2602.09850v2 Announce Type: replace Abstract: Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs)

Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation

arXiv:2605.06891v1 Announce Type: new Abstract: Labeled datasets reflect the biases of their annotation pipelines, which sometimes introduce label bias: group-conditional label errors that cause syste

safetyarxiv-cs-cv

Towards Highly-Constrained Human Motion Generation with Retrieval-Guided Diffusion Noise Optimization

arXiv:2605.08054v1 Announce Type: new Abstract: Generating human motion that satisfies customized zero-shot goal functions, enabling applications such as controllable character animation and behavior

Towards multi-modal forgery representation learning for AI-generated video detection and localization

arXiv:2605.07232v1 Announce Type: new Abstract: Recent advances in generative AI have democratized video creation at scale. AI-generated videos, including partially manipulated clips across visual and

local-aiarxiv-cs-cv

Applications

Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework

arXiv:2605.07429v1 Announce Type: new Abstract: Existing mobile devices are constrained by compact optical designs, such as small apertures, which make it difficult to produce natural, optically reali

applicationsarxiv-cs-cv

Agents

Towards Security-Auditable LLM Agents: A Unified Graph Representation

arXiv:2605.06812v1 Announce Type: new Abstract: LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and mult

agentsarxiv-cs-ai

TRACE: Tourism Recommendation with Accountable Citation Evidence

arXiv:2605.07677v1 Announce Type: cross Abstract: Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once

TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models

arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict

safetyarxiv-cs-lg

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

model-releasesarxiv-cs-cv

arXiv:2605.07593v1 Announce Type: new Abstract: Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams,

Agents

TraceFix: Repairing Agent Coordination Protocols with TLA+ Counterexamples

arXiv:2605.07935v1 Announce Type: new Abstract: We present TraceFix, a verification-first pipeline for Large Language Model (LLM) multi-agent coordination. An agent synthesizes a protocol topology as

agentsarxiv-cs-ai

Tracing the Arrow of Time: Diagnosing Temporal Information Flow in Video-LLMs

arXiv:2605.07568v1 Announce Type: cross Abstract: The Arrow-of-Time (AoT) task, determining whether a video plays forward or backward by recognizing temporal irreversibility, is one humans solve with

researcharxiv-cs-cl

Tracing Uncertainty in Language Model 'Reasoning'

arXiv:2605.07776v1 Announce Type: cross Abstract: Language model (LM) 'reasoning', commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics u

Tracking Large-scale Shared Bikes with Inertial Motion Learning in GNSS Blocked Environments

arXiv:2605.07412v1 Announce Type: cross Abstract: Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environmen

local-aiarxiv-cs-ai

Traffic Scenario Orchestration from Language via Constraint Satisfaction

model-releasesarxiv-cs-ro

arXiv:2605.06966v1 Announce Type: new Abstract: Autonomous vehicles (AVs) require extensive testing in simulation, but test case generation for driving scenarios is laborious. The desired scenarios ar

Training-Free Multimodal Large Language Model Orchestration

arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia

safetyarxiv-cs-cl

Training-Induced Escape from Token Clustering in a Mean-Field Formulation of Transformers

model-releasesarxiv-cs-lg

arXiv:2605.07772v1 Announce Type: new Abstract: Transformers perform inference by iteratively transforming token representations across layers. This layerwise computation has been studied empirically,

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation

arXiv:2605.07924v1 Announce Type: cross Abstract: Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Dis

TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations

arXiv:2605.06990v1 Announce Type: new Abstract: Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL

safetyarxiv-cs-cv

Tutorials

Transfer Learning Across Fast- and Full-Simulation Domains in High-Energy Physics

arXiv:2605.07471v1 Announce Type: new Abstract: Machine-learning models in high-energy physics are often trained on simulated data, where fully simulated samples are computationally expensive while fa

tutorialsarxiv-cs-lg

Transformer-Based Wildlife Species Classification from Daily Movement Trajectories

arXiv:2605.06726v1 Announce Type: new Abstract: Inferring the identity of wildlife species from daily movement data alone is a challenging task. We train sequence models on large-scale, 7-species GPS

researcharxiv-cs-lg

TRAS: An Interactive Software for Tracing Tree Ring Cross Sections

arXiv:2605.08025v1 Announce Type: new Abstract: Tree ring marking remains a key step in dendrometry and dendrochronology, but it is often performed manually, making the process time-consuming, subject

Applications

TraXion: Rethinking Pre-training Frameworks for Mobility and Beyond

arXiv:2605.06906v1 Announce Type: new Abstract: Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the join

applicationsarxiv-cs-lg

Tutorials

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders

arXiv:2605.07922v1 Announce Type: new Abstract: Learning hierarchical features in Sparse Autoencoders (SAEs) is essential for capturing the structured nature of real-world data and mitigating issues l

tutorialsarxiv-cs-lg

TriDE: Triangle-Consistent Translation Directions for Global Camera Pose Estimation

arXiv:2605.06889v1 Announce Type: new Abstract: Pairwise translation directions are a key input to camera location estimation in global structure-from-motion. Existing estimators usually process each

local-aiarxiv-cs-cv

TriP: A Triangle Puzzle Approach to Robust Translation Averaging

arXiv:2605.07143v1 Announce Type: new Abstract: Translation averaging aims to recover camera locations from pairwise relative translation directions and is a fundamental component of global Structure-

Tutorials

TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses

arXiv:2509.22813v2 Announce Type: replace Abstract: State Space Models (SSMs) have emerged as efficient alternatives to Vision Transformers (ViTs), with VMamba standing out as a pioneering architectur

tutorialsarxiv-cs-cv

TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models

arXiv:2601.18744v2 Announce Type: replace Abstract: Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the

TTF: Temporal Token Fusion for Efficient Video-Language Model

arXiv:2605.07355v1 Announce Type: cross Abstract: Video-language models (VLMs) face rapid inference costs as visual token counts scale with video length. For example, 32 frames at 448{imes}448 resolut

TUANDROMD-X: Advanced Entropy and Visual Analytics Dataset for Enhanced Malware Detection and Classification

arXiv:2605.06718v1 Announce Type: cross Abstract: Malware and malware-based attacks are becoming more prevalent and complex. Attackers regularly come up with new techniques that have the ability to ev

researcharxiv-cs-lg

Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting

arXiv:2605.06916v1 Announce Type: new Abstract: Probabilistic weather forecasting requires not only accurate trajectories, but calibrated distributions over plausible atmospheric futures. Recent data-

researcharxiv-cs-lg

UFT: Unifying Fine-Tuning of SFT and RLHF/DPO/UNA through a Generalized Implicit Reward Function

arXiv:2410.21438v3 Announce Type: replace Abstract: By pretraining on trillions of tokens, an LLM gains the capability of text generation. However, to enhance its utility and reduce potential harm, SF

safetyarxiv-cs-cl

UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types

arXiv:2408.15339v4 Announce Type: replace-cross Abstract: RL alignment methods, including RLHF and DPO, are primarily based on pairwise preference data. Although scalar or score-based feedback has bee

safetyarxiv-cs-cl

Uncertainty-Aware Structured Data Extraction from Full CMR Reports via Distilled LLMs

arXiv:2605.08045v1 Announce Type: new Abstract: Converting free-text cardiac magnetic resonance (CMR) reports into auditable structured data remains a bottleneck for cohort assembly, longitudinal cura

researcharxiv-cs-cl