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Taxonomy-aware deep learning for hierarchical marine species classification in underwater imagery

arXiv:2606.25989v1 Announce Type: new Abstract: Automated classification of marine species from underwater imagery is essential for scalable ocean biodiversity monitoring and conservation policy. Exis

safetyarxiv-cs-cv

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Taxonomy of Risks on Automated Fact-Checking Systems Considering its Propagation

DGX agent

arXiv:2606.25645v1 Announce Type: cross Abstract: In recent years, the posting of fake news including disinformation and misinformation on social networking services (SNS) has become a social problem.

tutorialsarxiv-cs-ai

25 Jun 2026

Teach-to-Reason: Competition-Guided Reasoning with a Self-Improving Teacher

arXiv:2606.25407v1 Announce Type: new Abstract: Chest X-ray visual question answering (CXR VQA) requires models not only to predict correct answers, but also to produce reliable medical reasoning. How

Tensorion: A Tensor-Aware Generalization of the Muon Optimizer

model-releasesarxiv-cs-cv

arXiv:2606.25975v1 Announce Type: cross Abstract: Common first-order optimizers, such as Adam, implicitly treat each parameter block as an unstructured vector, which disregards the multilinear weight

TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs

arXiv:2606.25545v1 Announce Type: new Abstract: Reconstructing diffusion tensors from sparse DWIs is critical for accelerating Diffusion Tensor Imaging (DTI) in clinical settings, yet current deep lea

Test-Time Adaptation in Optical Coherence Tomography Using Trajectory-Aligned Time-Independent Flow

arXiv:2606.18876v2 Announce Type: replace Abstract: Optical coherence tomography (OCT) is essential in ophthalmology, but inconsistent image quality especially in low-cost devices hinders automated an

applicationsarxiv-cs-cv

The 4/elta Bound: Designing Predictable LLM-Verifier Systems for Formal Method Guarantee

arXiv:2512.02080v3 Announce Type: replace-cross Abstract: The integration of Formal Verification tools with Large Language Models (LLMs) offers a path to scale software verification beyond manual work

The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing

arXiv:2606.25108v1 Announce Type: new Abstract: Autonomous AI systems are transitioning from advisory to autonomous roles for medication prescriptions. Recent United States bill H.R. 238 and Utah's pr

safetyarxiv-cs-ai

The cognitive, affective, and behavioral expression of self-stigma among people who use drugs in online substance use communities

arXiv:2606.25143v1 Announce Type: new Abstract: Objectives: To develop a codebook for self-stigma across cognitive, affective, and behavioral domains, and to estimate the prevalence, co-occurrence, an

The Effective Number of Nonzeros: Theory and Regularization for Sparse Recovery

arXiv:2603.13826v2 Announce Type: replace Abstract: Classical sparse recovery treats all nonzero entries equally, though numerical noise often creates long tails of negligible coefficients. This paper

The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms

arXiv:2606.25450v1 Announce Type: cross Abstract: Traditional evaluations measure a learning algorithm's final performance on an i.i.d. test set, reducing learning to a single aggregate score. This ap

The Gentle Collapse: Distributional Metrics for Continual Learning

arXiv:2606.25165v1 Announce Type: new Abstract: Accuracy degradation is the standard metric for Catastrophic Forgetting (CF), however, it records only whether forgetting occurred or not. It saturates

The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order

arXiv:2606.24993v1 Announce Type: new Abstract: Sequential learning is order-dependent: from Pile-style next-token domain adaptation to instruction-SFT and DPO, N candidate sources induce N! possible

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems

arXiv:2606.24937v1 Announce Type: cross Abstract: The Hitchhiker's Guide to Agentic AI is a comprehensive practitioner's reference for building autonomous AI systems. The book covers the full stack fr

safetyarxiv-cs-cl

The impact of artificial intelligence on enterprise software user roles

arXiv:2606.25525v1 Announce Type: cross Abstract: Artificial Intelligence (AI) is rapidly reshaping the nature of work in software development, transforming user roles, workflows, and collaboration pa

agentsarxiv-cs-ai

The Inference-Compute Frontier and a Latency-Efficient Architecture for Limit Order Book Prediction

arXiv:2606.25986v1 Announce Type: new Abstract: We study whether a scaling-law-style inference-compute frontier appears in limit order book prediction. Using FI-2010 and a suite of models ranging from

The Interplay of Harness Design and Post-Training in LLM Agents

arXiv:2606.25447v1 Announce Type: cross Abstract: Tool-integrated LLM agents are often wrapped within a harness: the scaffolding that determines which tools are exposed, how they are described, and wh

The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar

arXiv:2606.26015v1 Announce Type: new Abstract: Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities a

safetyarxiv-cs-cl

The Unfireable Safety Kernel: Execution-Time AI Alignment for AI Agents and Other Escapable AI Systems

arXiv:2606.26057v1 Announce Type: cross Abstract: AI agents are granted access to tools, APIs, and other infrastructure, making them active principals in those systems. The dominant approach places co

safetyarxiv-cs-lg

The Urysohn Ladder: Recursive Metric Contraction for Scalable Continual Learning

arXiv:2512.18471v2 Announce Type: replace Abstract: Continual learning systems face a fundamental geometric obstacle: as experience accumulates on a fixed-capacity manifold, covering numbers grow line

applicationsarxiv-cs-lg

TheoremGraph: Bridging Formal and Informal Mathematics

arXiv:2606.25363v1 Announce Type: cross Abstract: Mathematical knowledge is organized around statements and their dependencies, but this structure is exposed unevenly: informal papers cite mostly at t

agentsarxiv-cs-ai

Three Buddhist Vocabularies: Computational Stylometry of the English Pali Canon across Sutta, Vinaya, and Abhidhamma

model-releasesarxiv-cs-cl

arXiv:2606.25372v1 Announce Type: new Abstract: We present a computational stylometric analysis of the Tipitaka across all three Pitakas in English translation, extending earlier work on the Sutta Pit

TIDAL: Temporally Interleaved Diffusion and Action Loop for High-Frequency VLA Control

arXiv:2601.14945v2 Announce Type: replace Abstract: Large-scale Vision-Language-Action (VLA) models offer semantic generalization but suffer from high inference latency, limiting them to low-frequency

safetyarxiv-cs-ro

Tinker Tales: A Tangible Dialogue System for Child-AI Co-Creative Storytelling

arXiv:2602.04109v2 Announce Type: replace-cross Abstract: Conversational AI agents are increasingly explored as creative partners, yet how conversation design shapes child-AI dialogue in co-creative s

agentsarxiv-cs-ai

Local Ai

TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems

arXiv:2606.25627v1 Announce Type: new Abstract: Distributed intelligent systems increasingly need to train across data silos without centralizing raw data. Federated learning keeps data local but can

local-aiarxiv-cs-lg

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG

arXiv:2606.25191v1 Announce Type: cross Abstract: Multi-agent document assessment for retrieval-augmented generation is computationally expensive, driving practitioners toward smaller, deployable mode

agentsarxiv-cs-cl

To View Transform or Not to View Transform: NeRF-based Pre-training Perspective

arXiv:2603.28090v2 Announce Type: replace Abstract: Neural radiance fields (NeRFs) have emerged as a prominent pre-training paradigm for vision-centric autonomous driving, which enhances 3D geometry a

agentsarxiv-cs-cv

TokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems

arXiv:2606.25147v1 Announce Type: cross Abstract: User modeling in industrial recommender systems typically produces dense embeddings, which suffer from representational constraints inherent to fixed-

TopoCast: A Topological Fidelity Framework for Evaluating Transformer-Based Time Series Forecasting

arXiv:2606.25439v1 Announce Type: new Abstract: Deep learning-based models have achieved state-of-the-art performance in Time Series Forecasting (TSF), yet their evaluation remains dominated by pointw

Toten: A Knowledge-Based System For Structure-Preserving Representation Of Physical Quantities And Technical Notation In Brazilian Portuguese

model-releasesarxiv-cs-cl

arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expression

Toward Low-Latency Vision-Language Models with Doubly-Correct Predictions in Egocentric Visual Understanding

model-releasesarxiv-cs-cv

arXiv:2606.25160v1 Announce Type: cross Abstract: The rapid rise of Vision-Language Models (VLMs) in egocentric visual understanding has made low-latency inference in human-robot collaborative (HRC) t

Towards a Bathroom-Centered Human-Building Digital Twin Framework for Indoor Safety Analysis

arXiv:2606.23292v2 Announce Type: replace-cross Abstract: Bathroom use is a critical safety challenge for older adults because wet surfaces, constrained layouts, limited support, and frequent posture

safetyarxiv-cs-ai

Towards a Dynamic and Fixed-budget Memory Bank for Efficient Streaming Video Understanding

arXiv:2606.25658v1 Announce Type: new Abstract: Currently, streaming video understanding is still a daunting task for existing multimodal large language models (MLLMs). Its difficulties not only lie i

Towards Continuous Power Forecasting: Practical Continual Learning for Real-World Energy Systems in Nonstationary Time Series

arXiv:2606.24955v1 Announce Type: new Abstract: Power forecasting models deployed in real-world energy markets must operate under nonstationary conditions, where data distributions continually evolve

applicationsarxiv-cs-lg

Local Ai

Towards Robust EEG Decoding Based on Riemannian Self-Attention

arXiv:2606.25456v1 Announce Type: new Abstract: Brain-Computer Interface (BCI) based on electroencephalography (EEG) enables direct interaction between the brain and external environments and has sign

local-aiarxiv-cs-lg

Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models

arXiv:2606.24962v1 Announce Type: new Abstract: Recent progress in large-scale sequence modeling has shown that a single model can learn useful representations across highly diverse data distributions

safetyarxiv-cs-lg

Towards Structuring an Arabic-English Machine-Readable Dictionary Using Parsing Expression Grammars

arXiv:2606.25231v1 Announce Type: new Abstract: Dictionaries are rich sources of lexical information about words that is required for many applications of natural language processing and human languag

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

arXiv:2505.23866v2 Announce Type: replace Abstract: Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many stu

safetyarxiv-cs-lg

TRACER: Training-Free Closed-Loop Structured Inference for Traffic Accident Reconstruction

arXiv:2606.25002v1 Announce Type: new Abstract: Traffic accident reconstruction is a forensic inverse problem that requires recovering physically consistent motion from sparse and heterogeneous eviden

applicationsarxiv-cs-lg

Tracing Target Answers in Poisoned Retrieval Corpora via Token Influence Attribution

arXiv:2606.25721v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate model outputs through malicious retrieved docu

Training Dynamics of Neural Software Defect Predictors under Coupled Data-Quality Issues

arXiv:2606.24968v1 Announce Type: new Abstract: Context: Software defect prediction supports maintenance decisions such as testing prioritization, release-risk assessment, and quality monitoring. Howe

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models

arXiv:2606.25086v1 Announce Type: new Abstract: Many modern Language Model (LM) pipelines return an averaged model, such as an exponential moving average of the training iterates, rather than the fina

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR

arXiv:2606.25178v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has been extended from single-domain training to multi-domain reasoning suites spanning mathematic

safetyarxiv-cs-ai

Transferable Attack against Face Swapping in an Extended Space

arXiv:2606.25376v1 Announce Type: new Abstract: Although deep Face Swapping (FS) models may benefit the entertainment industry, they pose severe threats to privacy and security. Existing protections,

TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs

model-releasesarxiv-cs-cv

arXiv:2606.26029v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under co

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

researcharxiv-cs-ai

TryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy

arXiv:2606.26092v1 Announce Type: new Abstract: While Video Virtual Try-on (VVT) has achieved remarkable progress in synthesizing realistic garment overlays on dynamic subjects, existing paradigms rem

TTSA3R: Training-Free Temporal-Spatial Adaptive Persistent State for Streaming 3D Reconstruction

arXiv:2601.22615v3 Announce Type: replace Abstract: Streaming recurrent models enable efficient 3D reconstruction by maintaining persistent state representations. However, they suffer from catastrophi

safetyarxiv-cs-cv