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TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning

arXiv:2605.18109v1 Announce Type: new Abstract: In real home deployments, household agents must often operate from a complete household scene and a situated household request, rather than from a clean

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Model Releases

Taxonomy and Consistency Analysis of Safety Benchmarks for AI Agents

DGX agent

arXiv:2605.16282v1 Announce Type: cross Abstract: The rapid deployment of LLM-based autonomous agents has introduced safety risks that extend far beyond traditional LLM concerns, prompting a prolifera

model-releasesarxiv-cs-ai

19 May 2026

TClone: Low-Latency Forking of Live GUI Environments for Computer-Use Agents

arXiv:2605.17320v1 Announce Type: cross Abstract: Computer-use agents increasingly operate inside live personal workspaces, where their actions can modify files, applications, GUI state, credentials,

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?

arXiv:2605.18025v1 Announce Type: new Abstract: While Large Language Models have achieved remarkable integration in various vertical scenarios, their deployment in the telecommunications domain remain

Hardware

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval

arXiv:2502.20969v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external data sources to enhance factual correctness and domain

hardwarearxiv-cs-lg

Temporal Aware Pruning for Efficient Diffusion-based Video Generation

arXiv:2605.17837v1 Announce Type: cross Abstract: Video diffusion models have recently enabled high-quality video generation with ViT-based architectures, but remain computationally intensive because

Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations

model-releasesarxiv-cs-cl

arXiv:2605.17639v1 Announce Type: new Abstract: Co-citation structure is widely assumed to provide stable retrieval signal in legal information systems. We test this assumption longitudinally by const

Temporal Task Diversity: Inductive Biases Under Non-Stationarity in Synthetic Sequence Modelling

arXiv:2605.18281v1 Announce Type: new Abstract: Modern deep learning science often assumes that neural networks learn from a fixed data distribution. However, many practically important learning probl

safetyarxiv-cs-lg

Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction

arXiv:2605.16891v1 Announce Type: new Abstract: We introduce a tensor-channel equivariant graph neural network for direct prediction of molecular polarizability tensors. Building on the efficient PaiN

Tensor Cookbook: Mastering Tensors through Diagrams

arXiv:2605.16610v1 Announce Type: new Abstract: High-dimensional data arise naturally in many areas of science and engineering, including machine learning, signal processing, computational physics, an

tutorialsarxiv-cs-lg

Test-Time Hinting for Black-Box Vision-Language Models

arXiv:2605.16410v1 Announce Type: new Abstract: Test-time scaling (TTS) methods have proven highly effective for LLMs, yet their application to vision-language models (VLMs) remains relatively underex

researcharxiv-cs-cv

Testable and Actionable Calibration for Full Swap Regret

arXiv:2605.17749v1 Announce Type: new Abstract: AI generated predictions increasingly inform decision making in critical tasks, and therefore must be trustworthy. One widely used measure of trustworth

researcharxiv-cs-lg

Text2CAD-Bench: A Benchmark for LLM-based Text-to-Parametric CAD Generation

arXiv:2605.18430v1 Announce Type: new Abstract: Text-to-CAD generation aims to create parametric CAD models from natural language, enabling rapid prototyping and intuitive design workflows. However, e

The Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

Agents

The Alpha Illusion: Reported Alpha from LLM Trading Agents Should Not Be Treated as Deployment Evidence

arXiv:2605.16895v1 Announce Type: cross Abstract: End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgent

agentsarxiv-cs-ai

The Bayesian Geometry of Transformer Attention

arXiv:2512.22471v5 Announce Type: replace-cross Abstract: Transformers often appear to perform Bayesian reasoning in context, but verifying this rigorously has been impossible: natural data lack analy

The Capability Paradox: How Smarter Auditors Make Multi-Agent Systems Less Secure

arXiv:2605.17480v1 Announce Type: new Abstract: Multi-agent systems extend large language models (LLMs) by decomposing tasks among specialized agents, but their distributed decision process creates ne

The Diffusion Duality, Chapter II: Psi-Samplers

arXiv:2602.21185v2 Announce Type: replace Abstract: Uniform-state discrete diffusion models excel at few-step generation and guidance due to their ability to self-correct, making them preferred over a

tutorialsarxiv-cs-lg

Agents

The End of Trust: How Agentic AI Breaks Security Assumptions

arXiv:2605.16436v1 Announce Type: cross Abstract: For decades, the security of digital interaction has rested on an unacknowledged economic constraint. Attackers faced a tradeoff between the fidelity

agentsarxiv-cs-ai

The Expert Strikes Back: Interpreting Mixture-of-Experts Language Models at Expert Level

arXiv:2604.02178v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures have become the dominant choice for scaling Large Language Models (LLMs), activating only a subset of p

The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought

model-releasesarxiv-cs-cl

arXiv:2605.18079v1 Announce Type: cross Abstract: Existing expressivity results for transformers typically rely on hardmax attention, high precision, and other architectural modifications that disconn

The Frequency Confound in Language-Model Surprisal and Metaphor Novelty

arXiv:2605.06506v2 Announce Type: replace Abstract: Language-model (LM) surprisal is widely used as a proxy for contextual predictability and has been reported to correlate with metaphor novelty judgm

researcharxiv-cs-cl

The Geometry of Projection Heads: Conditioning, Invariance, and Collapse

arXiv:2605.17180v1 Announce Type: new Abstract: We develop a geometric theory of projection heads in self-supervised learning by modeling the head as a trainable Riemannian metric on the backbone repr

researcharxiv-cs-lg

The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaboration

arXiv:2605.18372v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in educational settings as interactive tools for collaboration. However, their tendency toward syco

The Illusion of Specialization: Unveiling the Domain-Invariant 'Standing Committee' in Mixture-of-Experts Models

arXiv:2601.03425v2 Announce Type: replace-cross Abstract: Mixture of Experts models are widely assumed to achieve domain specialization through sparse routing. In this work, we question this assumptio

The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit

arXiv:2605.16428v1 Announce Type: cross Abstract: Search engines traditionally complement online content platforms by directing users seeking information to external websites. The emergence of generat

The IsalProgram Programming Language

arXiv:2605.17008v1 Announce Type: cross Abstract: We introduce IsalProgram (Instruction Set and Language for Programming), a novel assembly-like programming language with three distinctive theoretical

Agents

The Journal of Prompt-Engineered (Moral) Philosophy Or: Why AI-Assisted Ethics Research Requires Process Transparency

arXiv:2511.08639v3 Announce Type: replace-cross Abstract: Existing AI disclosure mandates in scholarship require that AI assistance be reported but leave transparency philosophically unspecified: they

agentsarxiv-cs-ai

The Laplacian Keyboard: Beyond the Linear Span

arXiv:2602.07730v2 Announce Type: replace-cross Abstract: Across scientific disciplines, Laplacian eigenvectors serve as a fundamental basis for simplifying complex systems, from signal processing to

The Lattice Representation Hypothesis of Large Language Models

arXiv:2603.01227v2 Announce Type: replace Abstract: We propose the Lattice Representation Hypothesis of large language models: a symbolic backbone that grounds conceptual hierarchies and logical opera

The Learnability Gap in Medical Latent Diffusion

arXiv:2605.17087v1 Announce Type: new Abstract: Generative data augmentation with latent diffusion models is a promising strategy for addressing class imbalance in medical imaging, yet current approac

tutorialsarxiv-cs-cv

The Loupe: A Plug-and-Play Attention Module for Amplifying Discriminative Features in Vision Transformers

arXiv:2508.16663v2 Announce Type: replace-cross Abstract: Fine-Grained Visual Classification (FGVC) requires models to focus on subtle, task-relevant regions rather than broad object context. We prese

The MixCount Dataset: Bridging the Data Gap for Open-Vocabulary Object Counting

model-releasesarxiv-cs-cv

arXiv:2605.18063v1 Announce Type: new Abstract: Object counting is a foundational vision task with over a decade of dedicated research, yet state-of-the-art models still fail systematically in the mix

The Neural Tangent Kernel for Classification

arXiv:2605.17606v1 Announce Type: new Abstract: In wide neural networks, the Neural Tangent Kernel (NTK) remains approximately constant during training, providing a powerful theoretical tool for study

The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning

arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al

Local Ai

The Point of No Return: Counterfactual Localization of Deceptive Commitment in Language-Model Reasoning

arXiv:2605.17113v1 Announce Type: cross Abstract: Existing deception datasets label completed outputs as honest or deceptive, treating deception as a property of the final response rather than a funct

local-aiarxiv-cs-ai

The Powers of Precision: Structure-Informed Detection in Complex Systems -- From Customer Churn to Seizure Onset

arXiv:2601.21170v3 Announce Type: replace Abstract: Emergent phenomena -- onset of epileptic seizures, sudden customer churn, or pandemic outbreaks -- often arise from hidden causal interactions in co

The Range Shrinks, the Threat Remains: Re-evaluating LLM Package Hallucinations on the 2026 Frontier-Model Cohort

arXiv:2605.17062v1 Announce Type: cross Abstract: Spracklen et al. (USENIX Security '25) showed that code-generating large language models hallucinate package names that do not exist on PyPI or npm at

Applications

The Recovery Mechanism: Technology, Education, and What Happens When the Pattern Breaks

arXiv:2605.16283v1 Announce Type: cross Abstract: For centuries, each new technology has automated some layer of cognitive work and been absorbed by education retreating upward to teach the skills mac

applicationsarxiv-cs-ai

The Scaling Laws of Skills in LLM Agent Systems

arXiv:2605.16508v1 Announce Type: cross Abstract: As agent systems scale, skills accumulate into large reusable libraries, yet their scaling laws remain poorly understood. Across 15 frontier LLMs, 1,1

The Score Kalman Filter

arXiv:2605.16644v1 Announce Type: cross Abstract: A central obstacle in nonlinear Bayesian filtering is representing the belief distribution. Moment-based filters address this by propagating polynomia

researcharxiv-cs-lg

The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation

arXiv:2605.17500v1 Announce Type: cross Abstract: Generative text-to-image models are typically trained on large-scale web-scraped datasets that include diverse visual content such as copyrighted and

tutorialsarxiv-cs-cv

The Symmetries of Three-Layer ReLU Networks

arXiv:2605.18319v1 Announce Type: new Abstract: We develop a framework for analyzing parameter symmetries in deep ReLU networks and obtain a complete characterization of the generic parameter fibers f

The Token Games: Evaluating Language Model Reasoning with Puzzle Duels

arXiv:2602.17831v2 Announce Type: replace Abstract: Evaluating the reasoning capabilities of Large Language Models is increasingly challenging as models improve. Human curation of hard questions is hi

The Unlearnability Phenomenon in RLVR for Language Models

arXiv:2605.16787v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) has proven effective in improving Large Language Model's (LLM) reasoning ability. However, the le

researcharxiv-cs-cl

'The Whole Is Greater Than the Sum of Its Parts': A Compatibility-Aware Multi-Teacher CoT Distillation Framework

arXiv:2601.13992v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) reasoning empowers Large Language Models (LLMs) with remarkable capabilities but typically requires prohibitive paramet

Theory of Minimal Weight Perturbations in Deep Networks and its Applications for Low-Rank Activated Backdoor Attacks

arXiv:2601.16880v2 Announce Type: replace Abstract: The minimal norm weight perturbations of DNNs required to achieve a specified change in output are derived and the factors determining its size are

Therapist-Exoskeleton-Patient Interaction for Gait Therapy

arXiv:2507.16059v2 Announce Type: replace Abstract: Following a stroke, individuals often experience mobility and balance impairments due to lower-limb weakness and loss of independent joint control.

tutorialsarxiv-cs-ro