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The Latent Diagnostic Taxonomy: A Framework for Constructing Classifiers and Diagnosing Their Decisions, Applied to Prompt Injection Detection

arXiv:2608.26423v1 Announce Type: cross Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for developing a complementary diagnostic that identifies whic

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The Reasoning Tax: Token Economics of LLM Reasoning Across Task Types and Deployment Contexts

DGX agent

arXiv:2608.26235v1 Announce Type: new Abstract: Accuracy-only benchmarking of reasoning-capable large language models misses a central deployment question: when do extended thinking tokens earn their

model-releasesarxiv-cs-ai

28 Aug 2026

The Score Granularity Gap in Black-Box LLM Classification: A Comparative Study of Confidence Constructions

arXiv:2606.22179v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as black-box classifiers in pipelines that automate confident decisions and route uncertain o

The Thousand-Graph Hypothesis: A Testable Hypothesis of Task-Conditioned Relation Materialization in Repository-Level Code Reasoning

arXiv:2608.26602v1 Announce Type: cross Abstract: Large software repositories are often beyond model context limits. Training repository knowledge into models is costly and quickly stale, while local

Think3D: Thinking with Space for Spatial Reasoning

arXiv:2601.13029v4 Announce Type: replace Abstract: While Vision-Language Models (VLMs) excel at 2D visual understanding, they remain constrained by 2D-centric paradigm that severely limits genuine 3D

Agents

Thinking on Shots: Consistent Multi-Shot Video Editing with Agentic Reasoning

arXiv:2608.26809v1 Announce Type: new Abstract: While generative AI has significantly advanced video editing, existing methods primarily focus on single-shot or short video clips. Editing long videos

agentsarxiv-cs-cv

Thomson: Continual Learning of Frontier Models for SovereignAI

arXiv:2608.27147v1 Announce Type: new Abstract: The development of frontier models is commonly perceived to be the exclusive remit of a small number of heavily funded players, creating an information,

Tissue-Mixture Entropy-Weighted Reconstruction for Partial-Volume-Aware Brain MRI Super-Resolution

arXiv:2608.26647v1 Announce Type: new Abstract: Full-image objectives in brain magnetic resonance imaging (MRI) super-resolution (SR) can underweight tissue-transition regions affected by the partial-

Applications

Token-Level Advertising

arXiv:2608.27382v1 Announce Type: cross Abstract: Generative AI is transforming how people access information, challenging traditional advertising mechanisms built around predefined slots. Towards gen

applicationsarxiv-cs-lg

TopiCLEAR: Adaptive embedding clustering for interpretable topic discovery from short texts

arXiv:2512.06694v2 Announce Type: replace Abstract: Topic discovery is a fundamental technique for text mining that identifies abstract topics within large document collections. A recent approach to t

Toward a New Science of AI as Cognitive Infrastructure

arXiv:2507.22893v3 Announce Type: replace-cross Abstract: Contemporary human-AI interaction research overlooks how AI systems fundamentally reshape human cognition pre-consciously, a critical blind sp

researcharxiv-cs-ai

Toward all-optical unsupervised Hebbian learning in deep photonic neuromorphic networks

arXiv:2601.22300v4 Announce Type: replace-cross Abstract: We propose a deep photonic neuromorphic network (PNN) architecture based on phase-change material (PCM) synapses and local optical feedback fo

local-aiarxiv-cs-lg

Toward Equitable Low-Carbon Mobility: Fairness-Aware Demand Prediction for Expanding Bike-Sharing Systems

arXiv:2608.26451v1 Announce Type: new Abstract: Bike-sharing systems are an important component of low-carbon urban mobility, but continued expansion creates challenges in both cold-start prediction a

safetyarxiv-cs-lg

Towards a universal meta-optics solver via large language models

model-releasesarxiv-cs-lg

arXiv:2608.26417v1 Announce Type: cross Abstract: Metasurface design increasingly requires fast models that can operate across structurally distinct device families, rather than retraining a separate

Agents

Towards Expert Financial QA via Self-Improving RAG

arXiv:2608.26706v1 Announce Type: new Abstract: Expert-level financial question answering requires both grounded verification to catch numeric hallucinations and audit trails for regulatory compliance

agentsarxiv-cs-cl

Towards Interpretable Depression Detection: Linking Acoustic Features to DSM-5 Indicators

arXiv:2608.26148v1 Announce Type: new Abstract: Depression affects millions worldwide, yet diagnosis relies on subjective self-reports that may miss authentic behavior. This paper presents an approach

Tutorials

TRACE-CRC: Trajectory-Adaptive Conformal Risk Control for Multi-Step Channel State Information Prediction

arXiv:2608.27124v1 Announce Type: new Abstract: Reliable prediction of time-varying channel state information (CSI) is essential for efficient wireless communication. Each CSI frame is a matrix-valued

tutorialsarxiv-cs-lg

TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing

arXiv:2608.26219v1 Announce Type: cross Abstract: Reconstructing continuous physical fields from sparse measurements is central to scientific monitoring, inverse modeling, and digital-twin constructio

local-aiarxiv-cs-lg

TraceBench: Controlled Evaluation of LLM Agents for Time-Series Root-Cause Attribution

model-releasesarxiv-cs-lg

arXiv:2608.27182v1 Announce Type: new Abstract: LLM agents are increasingly applied to anomaly detection and root-cause analysis in time-series observations collected from real-world systems; however,

Training-Time Explainability for Multilingual Hate Speech Detection: Aligning Model Reasoning with Human Rationales

arXiv:2608.26125v1 Announce Type: cross Abstract: Online hate against Muslim communities often appears in culturally coded, multilingual forms that evade conventional AI moderation. Such systems, thou

Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties

arXiv:2603.25489v2 Announce Type: replace Abstract: Recent strategies for low-resource machine translation rely on LLMs to generate synthetic data based on text in higher-resource languages. We revisi

TransMeme: A Multi-Agent Framework for Cross-Cultural Meme Transcreation

arXiv:2608.27127v1 Announce Type: new Abstract: Internet memes are a pervasive form of multimodal online communication; however, such communication often involves users from diverse linguistic and cul

TrapVLA: Trapping Vision-Language-Action Models in Configured Failure Modes

arXiv:2608.26578v1 Announce Type: cross Abstract: This work introduces Configured Failure Trapping, a novel backdoor attack task against Vision-Language-Action (VLA) models, which aims to activate att

safetyarxiv-cs-cv

TreeGraft: Adaptive Multi-Drafter Grafting for Tree-Based Speculative Decoding

arXiv:2608.26112v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference through a draft-then-verify paradigm. Building on this, tree-structured methods improve

TTPO: Test-Time Policy Optimization

arXiv:2608.27448v1 Announce Type: new Abstract: Recent prominent post-training methods, such as Reinforcement Learning (RL) and On-Policy Self-Distillation (OPSD), have driven rapid progress in mathem

safetyarxiv-cs-cl

Applications

TutorTrace: A Dataset and Taxonomy for Classifying Learner Behavioral States during AI-Assisted Programming Education

arXiv:2608.26184v1 Announce Type: new Abstract: AI programming tutors provide scalable support, yet lack the behavioral context human tutors rely on to adapt support to learners' needs. We present Tut

applicationsarxiv-cs-ai

TwinKV: A Composable Repair Pass for KV Cache Eviction via Pairwise Key Redundancy

arXiv:2608.27128v1 Announce Type: new Abstract: Long-context inference is bottlenecked by the memory footprint of the key-value (KV) cache, especially for small models under tight resource budgets. Ex

UCB for Large-Scale Pure Exploration: Beyond Sub-Gaussianity

arXiv:2511.22273v2 Announce Type: replace-cross Abstract: Selecting the best alternative from a finite set is the central objective of ranking and selection (R&S) and best arm identification (BAI). Tr

researcharxiv-cs-lg

UFO-DETR: Frequency-Guided End-to-End Detector for UAV Tiny Objects

arXiv:2602.22712v2 Announce Type: replace Abstract: Small target detection in UAV imagery faces significant challenges such as scale variations, dense distribution, and the dominance of small targets.

researcharxiv-cs-cv

Ultra Low-Power, Lightweight, Probabilistic RSS-Based Path Reconstruction: A System for Landscape-Scale Bee Tracking

arXiv:2608.27152v1 Announce Type: new Abstract: Applications in fields such as movement ecology, Internet of Things or robotics share the need for systems that localize devices that are too small and

local-aiarxiv-cs-lg

Understanding Evolution Strategies for LLM Reasoning: Broader Reasoning Coverage than GRPO

model-releasesarxiv-cs-lg

arXiv:2608.27351v1 Announce Type: new Abstract: Evolution Strategies (ES) have recently emerged as a memory-efficient post-training paradigm for LLM reasoning. However, the optimization behavior of ES

Tutorials

UniFLM: United Segmentation and Measurement on Fetal Limb Ultrasonic Image

arXiv:2608.27240v1 Announce Type: new Abstract: Prenatal ultrasound examination is crucial for assessing fetal limb development and detecting congenital anomalies. However, existing artificial intelli

tutorialsarxiv-cs-cv

Unifying Detection and Adaptation in Task-Free Continual Learning

arXiv:2608.27070v1 Announce Type: cross Abstract: To mitigate catastrophic forgetting in downstream continual learning (CL) for large language models (LLMs), existing methods typically constrain param

UniGeo: A Multi-modal Large Language Model for Text-Guided Cross-View Geo-Localization

arXiv:2608.26722v1 Announce Type: new Abstract: Text-guided drone geo-localization aims to identify a target region in a large-scale image gallery from a natural-language description. Existing methods

local-aiarxiv-cs-cv

Universality and sharp thresholds for ellipsoid fitting

arXiv:2608.27372v1 Announce Type: cross Abstract: We establish a sharp phase transition for fitting random vectors by an ellipsoid. The random vectors have independent subgaussian coordinates with mea

researcharxiv-cs-lg

Unsupervised Adaptation of 3D CT Foundation Models for 3D CBCT Segmentation

arXiv:2608.27190v1 Announce Type: new Abstract: Accurate 3D segmentation of cone-beam CT (CBCT) is critical for interventional and radiation therapy applications, yet it remains limited by two compoun

safetyarxiv-cs-cv

UrbanGround: From Local Perception to Spatial Agency in a Real-Scale City

arXiv:2608.27456v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can interpret a street view, but urban agency depends on whether such local evidence remains useful after the a

local-aiarxiv-cs-cv

Using Poly-Encoders for Computationally Efficient Automated Creativity Assessment

arXiv:2608.26165v1 Announce Type: cross Abstract: Automated creativity assessment has been a long standing challenge, with traditional methods often being resource intensive or lacking practical accur

researcharxiv-cs-ai

Using VLM Reasoning to Constrain Task and Motion Planning

arXiv:2510.25548v3 Announce Type: replace Abstract: In task and motion planning, high-level task planning is done over an abstraction of the world to enable efficient search in long-horizon robotics p

researcharxiv-cs-ro

Vagdhenu: A Vrutta (Meter) Aware Shloka-to-Chant (TTS) System for Sanskrit

arXiv:2608.26146v1 Announce Type: new Abstract: We present Vagdhenu, a vrutta (meter) aware shloka-to-chant system for Sanskrit: a text-to-speech system that maps a metrical verse to its chanted paray

Agents

Verify Smarter, Evolve Further: Efficient Harness Evolution through Behavior-Aware Verification

arXiv:2608.27311v1 Announce Type: new Abstract: Agent harnesses shape how language-model agents use instructions, tools, and runtime components, but adapting these harnesses requires costly verificati

agentsarxiv-cs-ai

VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation

arXiv:2608.26155v1 Announce Type: cross Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limi

Video-FLAIR: Not Whether to Reason, But How

arXiv:2608.26495v1 Announce Type: new Abstract: Multimodal queries can require different types of reasoning. Some can be answered via perceptual reasoning, extracting information directly from the vis

researcharxiv-cs-cv

Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

arXiv:2608.27065v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has recently emerged as an effective post-training paradigm that improves policy optimization through dense token-lev

safetyarxiv-cs-cv

VIPER: An Expert-Curated Benchmark for Vision-Language Models in Veterinary Pathology

arXiv:2608.26382v1 Announce Type: new Abstract: Pathology vision-language models are advancing rapidly, yet existing benchmarks remain focused on human tissue, particularly oncology, leaving non-human

Virtual iEEG from Scalp EEG: Charting the Landscape of Source Imaging, Intracranial Inference and Reconstruction

arXiv:2608.26998v1 Announce Type: new Abstract: Intracranial electroencephalography (iEEG) provides temporally precise and spatially specific access to neural activity from focal and deep brain region

researcharxiv-cs-cv

Vision-centric generative AI models: A software-hardware perspective

arXiv:2608.27199v1 Announce Type: new Abstract: Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal mode

Visual Information-Guided Parallel Decoding for Diffusion Multimodal Large Language Models

arXiv:2608.26580v1 Announce Type: cross Abstract: Diffusion multimodal large language models (dMLLMs) have recently emerged as a new decoding paradigm for multimodal generation. Starting from a fully