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SynCB: A Synergy Concept-Based Model with Dynamic Routing Between Concepts and Complementary Neural Branches

arXiv:2605.20908v1 Announce Type: new Abstract: Concept-based (CB) models provide interpretability and support test-time human intervention, while standard neural networks (NN) offer strong task perfo

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Synchronization and Turn-Taking in Full-Duplex Speech Dialogue Models

DGX agent

arXiv:2605.20356v1 Announce Type: new Abstract: Full-duplex spoken dialogue models (SDMs) can listen and speak simultaneously, enabling interaction dynamics closer to human conversation than turn-base

safetyarxiv-cs-cl

21 May 2026

TabPFN Extensions for Interpretable Geotechnical Modelling

arXiv:2603.21033v2 Announce Type: replace-cross Abstract: Geotechnical site characterisation relies on sparse, heterogeneous borehole data, where uncertainty quantification and interpretability matter

TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data

arXiv:2605.20234v1 Announce Type: new Abstract: Prior-Data Fitted networks (PFNs) have been very successful in tabular contexts, handling prediction tasks in context. However, they are designed for si

Task-conditioned probing of instruction-tuned multimodal LLMs: Region-specific brain alignment patterns under naturalistic stimuli

arXiv:2506.08277v3 Announce Type: replace-cross Abstract: Recent voxel-wise multimodal brain encoding studies have shown that multimodal large language models (MLLMs) exhibit a higher degree of brain

safetyarxiv-cs-cl

Tutorials

Task-Routed Mixture-of-Experts with Cognitive Appraisal for Implicit Sentiment Analysis

arXiv:2605.20916v1 Announce Type: new Abstract: Implicit sentiment analysis is challenging because sentiment toward an aspect is often inferred from events rather than expressed through explicit opini

tutorialsarxiv-cs-cl

TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design

arXiv:2605.20731v1 Announce Type: new Abstract: Text-to-image models produce graphic design at production scale, but their supervision comes from photo-style preference data with a single overall verd

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis

arXiv:2510.06063v2 Announce Type: replace-cross Abstract: Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventio

applicationsarxiv-cs-lg

TelePhysics: Physics-Grounded Multi-Object Scene Generation from a Single Image with Real-Time Interaction

arXiv:2605.20290v1 Announce Type: cross Abstract: Recent generative video models achieve impressive visual quality but remain constrained by limited physical consistency and controllability. Existing

safetyarxiv-cs-cv

TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos

arXiv:2605.21443v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing eval

Temporal Counterfactual Explanations of Behaviour Tree Decisions

arXiv:2509.07674v2 Announce Type: replace Abstract: Explainability, in particular, the ability for robots to explain why they have made a decision or behaved in a certain way, is a critical tool in he

researcharxiv-cs-ro

TERDNet: Transformer Encoder-Recurrent Decoder Network for Scene Change Detection

arXiv:2605.20822v1 Announce Type: new Abstract: In this work, we address the challenge of Scene Change Detection (SCD), where the goal is to identify variations between two images of the same location

applicationsarxiv-cs-cv

Terminal-World: Scaling Terminal-Agent Environments via Agent Skills

arXiv:2605.20876v1 Announce Type: new Abstract: Terminal agents extend Large Language Models with the ability to execute tasks directly in command-line environments, but their progress is bottlenecked

Terrestrial Soft Mobile Robots: A Review

arXiv:2605.20304v1 Announce Type: new Abstract: Soft mobile robots have emerged as a promising area of research with potential applications in various disciplines including but not limited to search-a

applicationsarxiv-cs-ro

Testing Support Size More Efficiently Than Learning Histograms

arXiv:2410.18915v4 Announce Type: replace-cross Abstract: Consider two problems about an unknown probability distribution p: 1. How many samples from p are required to test if p is supported on n elem

Text Analytics Evaluation Framework: A Case Study on LLMs and Social Media

arXiv:2605.21338v1 Announce Type: new Abstract: LLMs have demonstrated exceptional proficiency in a wide range of NLP tasks. However, a notable gap remains in practical data analysis scenarios, partic

TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization

arXiv:2605.21318v1 Announce Type: new Abstract: Large language models (LLMs) are highly sensitive to the prompts used to specify task objectives and behavioral constraints. Many recent prompt optimiza

TextSculptor: Training and Benchmarking Scene Text Editing

arXiv:2605.21090v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and diffusion-based generative models have substantially improved prompt-driven image editin

The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure?

arXiv:2605.20749v1 Announce Type: new Abstract: Gated Linear Units (GLU) and their variants are widely adopted in modern open-source large language model architectures and consistently outperform thei

The Economics of AI Inference: Inflation Dynamics, Welfare Costs, and Optimal Monetary Policy under the Inference-Cost Phillips Curve

arXiv:2605.20281v1 Announce Type: cross Abstract: We develop a unified microeconomic and monetary theory of artificial intelligence inference costs and their pass-through to inflation, welfare, and op

safetyarxiv-cs-lg

The Economics of Model Collapse: Equilibrium, Welfare, and Optimal Provenance Subsidies in Synthetic Data Markets

arXiv:2605.20279v1 Announce Type: cross Abstract: Generative artificial intelligence is rapidly transforming the supply side of training data: an increasing share of new tokens, images, and structured

Local Ai

The General Theory of Localization Methods

arXiv:2605.20635v1 Announce Type: new Abstract: This paper proposes a general machine learning framework called the localization method, which is fundamentally built on two core concepts: localization

local-aiarxiv-cs-lg

The Generation-Recognition Asymmetry: Six Dimensions of a Fundamental Divide in Formal Language Theory

arXiv:2603.10139v2 Announce Type: replace Abstract: Every formal grammar defines a language and can in principle be used in three ways: to generate strings (production), to recognize them (parsing), o

applicationsarxiv-cs-cl

The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering

arXiv:2605.20745v1 Announce Type: cross Abstract: Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they

The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study

arXiv:2605.20767v1 Announce Type: new Abstract: Large language models (LLMs) show potential as simulators of human behavior, offering a scalable way to study responses to interventions. However, becau

safetyarxiv-cs-cl

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

arXiv:2510.08482v3 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual ground

The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents

arXiv:2605.20544v1 Announce Type: cross Abstract: Vision-language models (VLMs) are used as high-level planners for embodied agents, translating natural language instructions and visual observations i

Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference

arXiv:2605.21253v1 Announce Type: cross Abstract: Compositional score-based approaches to simulation-based inference (SBI) approximate the posterior over a shared parameter given n independent observa

THEval. Evaluation Framework for Talking Head Video Generation

arXiv:2511.04520v4 Announce Type: replace Abstract: Video generation has achieved remarkable progress, with generated videos increasingly resembling real ones. However, the rapid advance in generation

Thinking-while-speaking: A Controlled, Interleaved Reasoning Method for Real-Time Speech Generation

arXiv:2605.20946v1 Announce Type: new Abstract: The thinking-while-speaking paradigm aims to make AI communication more human. A key challenge is maintaining fluent speech while performing deep reason

Time-Dependent PDE-Constrained Optimization via Weak-Form Latent Dynamics

arXiv:2605.20639v1 Announce Type: cross Abstract: Optimization problems constrained by high-dimensional, time-dependent partial differential equations require repeated forward and sensitivity solves,

Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting

arXiv:2506.17631v4 Announce Type: replace Abstract: Time series forecasting aims to model temporal dependencies among variables for future state inference, holding significant importance and widesprea

safetyarxiv-cs-lg

Time-To-Reach Separation and Safety Filtering for Safe, Fair, and Efficient Multi-Agent Coordination

arXiv:2605.20625v1 Announce Type: cross Abstract: Advanced Air Mobility (AAM) operations are expected to significantly increase aerial traffic in urban airspace, requiring autonomous traffic managemen

safetyarxiv-cs-ro

TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health

arXiv:2605.21295v1 Announce Type: new Abstract: Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfit

Tiny-Engram: Trigger-Indexed Concept Tables for Generative Vision

arXiv:2605.20309v1 Announce Type: new Abstract: Current personalization methods for generative vision models typically encode new concepts through continuous adapters or weight updates, yet provide li

researcharxiv-cs-cv

Tippett-minimum Fusion of Representation-space Diffusion Models for Multi-Encoder Out-of-Distribution Detection

arXiv:2605.20502v1 Announce Type: cross Abstract: We address out-of-distribution (OOD) detection across the full spectrum of distribution shifts -- global domain changes, semantic divergence, texture

To Select or not to Select, that is the Question: Distilling Robot Skill Prediction into a Small Ensemble

model-releasesarxiv-cs-ro

arXiv:2605.21242v1 Announce Type: new Abstract: As robot fleets become more heterogeneous, including humanoids, rovers, quadrupeds, and drones, selecting the right robot for a task becomes a core syst

torchtune: PyTorch native post-training library

arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f

Towards Context-Invariant Safety Alignment for Large Language Models

arXiv:2605.20994v1 Announce Type: new Abstract: Preference-based post-training aligns LLMs with human intent, yet safety behavior often remains brittle. A model may refuse a harmful request in a stand

safetyarxiv-cs-cl

Towards Integrated Rock Support Visualisation in 3D Point Cloud of Underground Mines

arXiv:2605.20973v1 Announce Type: new Abstract: The effectiveness of rock support in underground mines depends on the interaction between installed rock bolts and the structural fabric of the surround

researcharxiv-cs-cv

Agents

Towards Physically Consistent 4D Scene Reconstruction for Closed-loop Autonomous Driving Simulation

arXiv:2605.21032v1 Announce Type: new Abstract: High-fidelity street scene reconstruction is pivotal for end-to-end autonomous driving simulation, where novel-view synthesis (NVS) and time-varying inf

agentsarxiv-cs-cv

Agents

Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

arXiv:2605.21395v1 Announce Type: cross Abstract: The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster,

agentsarxiv-cs-lg

Towards the Anonymization of the Language Modeling

arXiv:2501.02407v3 Announce Type: replace Abstract: Rapid advances in Natural Language Processing (NLP) have revolutionized many fields, including healthcare. However, these advances raise significant

applicationsarxiv-cs-cl

Towards UAV Detection in the Real World: A New Multispectral Dataset UAVNet-MS and a New Method

arXiv:2605.20963v1 Announce Type: new Abstract: The proliferation of unmanned aerial vehicles (UAVs) has created urgent demand for precise UAV monitoring. Existing RGB-based systems rely on spatial cu

Tutorials

Towards Understanding Self-Pretraining for Sequence Classification

arXiv:2605.21070v1 Announce Type: new Abstract: Amos et al. (2024) showed that the accuracy of Transformer models in sequence classification can be significantly improved by first pretraining with a m

tutorialsarxiv-cs-lg

Toxic Subword Pruning for Dialogue Response Generation on Large Language Models

arXiv:2410.04155v2 Announce Type: replace Abstract: How to defend large language models (LLMs) from generating toxic content is an important research area. Yet, most research focused on various model

Tracing the ongoing emergence of human-like reasoning in Large Language Models

arXiv:2605.21299v1 Announce Type: new Abstract: Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is typically understood as implying that the speaker

Training distribution determines the ceiling of drug-blind cancer sensitivity prediction

arXiv:2605.20885v1 Announce Type: new Abstract: Precision oncology requires predicting which drugs will suppress a specific tumor from its molecular profile, but drug-blind sensitivity prediction has