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arXiv:2603.25165v3 Announce Type: replace Abstract: Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Exi

tutorialsarxiv-cs-cv

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Safety

Towards Identifying the Dataset Biases Causing Phantom Transfer

DGX agent

arXiv:2609.14449v1 Announce Type: new Abstract: Recent work has shown that a teacher model can transfer a bias to a student through a dataset from which every explicit reference to that bias has been

safetyarxiv-cs-lg

15 Sept 2026

Towards Optimizing SQL Generation via LLM Routing

arXiv:2411.04319v1 Announce Type: cross Abstract: Text-to-SQL enables users to interact with databases through natural language, simplifying access to structured data. Although highly capable large la

Hardware

Towards Practical Precision Agriculture: Real-Time Fruit Detection and Video Analytics on Embedded Edge Hardware

arXiv:2609.13551v1 Announce Type: new Abstract: Static-image benchmarks do not capture the computational and temporal requirements of practical orchard video analytics. This study presents an end-to-e

hardwarearxiv-cs-cv

TRACE: Two-Stage Detector-Response Estimation With Angular Cosine Expansion for Ring Artifact Correction in Photon-Counting CT

arXiv:2609.15834v1 Announce Type: new Abstract: Detector response nonuniformity introduces systematic projection errors and ring artifacts in photon-counting detector computed tomography (PCD-CT). In

safetyarxiv-cs-cv

Tracking the Ground: Online Lidar Identification of Robot-Induced Soil Deformation in Agricultural Environments

arXiv:2609.15667v1 Announce Type: new Abstract: Agriculture faces many challenges, and robotic systems can play an important role in addressing them by improving the efficiency and sustainability of f

researcharxiv-cs-ro

Tracking Through Decoupling Singularities: A Singularity-Robust Homotopy-Continuation Extension of Feedback Linearization

model-releasesarxiv-cs-ro

arXiv:2607.10436v3 Announce Type: replace-cross Abstract: Input--output feedback linearization fails at decoupling singularities, where the decoupling matrix loses rank, the relative degree is lost, a

TRACTA: Benchmarking Temporal Reasoning over Semantic Trajectories

arXiv:2607.22365v2 Announce Type: replace Abstract: High-complexity operational environments require methods that characterize temporally distributed patterns rather than classify isolated events. Thi

Training Specialist Models without Reasoning Trajectories for Domain Expert Distillation

arXiv:2609.13770v1 Announce Type: cross Abstract: Specialist distillation effectively transfers domain expertise to student models via teacher-generated reasoning trajectories. However, when these spe

researcharxiv-cs-cl

Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks

Transforming harmonic coefficients for 3D splat compression

arXiv:2609.15735v1 Announce Type: cross Abstract: We address the problem of color attribute compression for 3D splats. We show that all images generated by 3D splats are linear in the coefficients for

Translating the Translator: Decomposing the Cost of English-Forced Inter-Agent Communication

arXiv:2609.15079v1 Announce Type: cross Abstract: Multi-agent LLM architectures, such as LangChain and AutoGen, largely assume English as the lingua franca for internal inter-agent communication, even

agentsarxiv-cs-ai

Translation-Invariant Tile-Based Phase Unwrapping with Residual-Weighted Multipath Averaging

arXiv:2609.13409v1 Announce Type: cross Abstract: Phase unwrapping is a key step in interferometric and coherent imaging, where the physical quantity of interest is carried by a phase that the instrum

TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps

arXiv:2609.14762v1 Announce Type: cross Abstract: Cloud-hosted large language models (LLMs) are increasingly used for root cause analysis (RCA) in AIOps pipelines, but they introduce data privacy risk

Trust-Region Neural Moving Horizon Estimation for Robots

arXiv:2309.05955v5 Announce Type: replace Abstract: Accurate disturbance estimation is essential for safe robot operations. The recently proposed neural moving horizon estimation (NeuroMHE), which use

safetyarxiv-cs-ro

Trustworthy Agentic AI: A Comprehensive Cybersecurity and Systems Survey on Threat Landscapes, Defense Architectures, and Open Challenges

arXiv:2609.13731v1 Announce Type: new Abstract: The transition from passive foundation models to autonomous, goal-directed agentic AI systems has introduced unprecedented capabilities by coupling recu

Trustworthy, Explainable, and Sustainable Decentralized Intelligence for 6G Networks

arXiv:2609.13872v1 Announce Type: cross Abstract: As 6G networks transition from theoretical frameworks into operational realities, artificial intelligence (AI) evolves from an add-on optimization too

TryOnReward: Learning Foveated Consistency for Reinforcement Fine-Tuning of Virtual Try-On

arXiv:2609.13259v1 Announce Type: cross Abstract: Virtual Try-On (VTON) aims to dress a person with the reference garment, producing visually reasonable results aligned with human preferences. Turning

TTDF: A Two-Stage Framework for Reliable Surgical Phase Transition Detection

arXiv:2609.14624v1 Announce Type: new Abstract: Reliable workflow transition detection is important for context-aware surgical assistance and downstream decision support. However, online surgical phas

Turkish MMLU Pro: Traceable Option Augmentation and Its Validity Limits in Turkish Multiple-Choice Evaluation

arXiv:2609.15467v1 Announce Type: cross Abstract: Adding answer options can lower multiple-choice scores without improving assessment validity. Turkish MMLU Pro examines this distinction using 12,000

agentsarxiv-cs-ai

TwinICL: Diagnosing Multimodal In-Context Learning through Paired Counterfactuals

arXiv:2609.15028v1 Announce Type: new Abstract: In-context learning (ICL) enables models to infer tasks from demonstrations, but existing benchmarks generally lack matched text and image versions need

Two-Stage Mixture-of-LoRA for Multi-Task Medical Vision-Language Learning

arXiv:2609.14350v1 Announce Type: new Abstract: Medical vision-language models (VLMs) allow a single model to perform clinical image analysis tasks ranging from diagnosis classification to report gene

Two-Stage Personalized Gait Phase Estimation in Stroke Survivors During Exoskeleton-Assisted Walking: An Offline Feasibility Study

arXiv:2609.14984v1 Announce Type: new Abstract: This study evaluated personalized gait phase estimation for stroke survivors using functional inertial measurement unit (IMU) alignment and two-stage se

safetyarxiv-cs-ro

TyPatch: Transforming Patches into Typestate Rules for Kernel Bug Detection

arXiv:2609.13728v1 Announce Type: cross Abstract: Historical Linux kernel patches capture defect knowledge that applies beyond their original repair sites. Recent work has shown that large language mo

Hardware

Typhoon ASR Streaming: Steerable Low-Latency Thai Speech Recognition with Real-Time Shallow Fusion

arXiv:2609.14991v1 Announce Type: new Abstract: Open Thai automatic speech recognition (ASR) is dominated by offline, Whisper-based models that read the whole utterance before transcribing, ruling out

hardwarearxiv-cs-cl

TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series

arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must

Uncertainty-Aware Calibrated Clinical Text Classification with Large Language Models

arXiv:2509.19375v2 Announce Type: replace-cross Abstract: Large language models are increasingly used for clinical text classification, where overconfident misclassifications can directly affect patie

Uncertainty-Guided Sparse Refinement for Action Chunking Transformer Policies

model-releasesarxiv-cs-ro

arXiv:2609.15840v1 Announce Type: new Abstract: Learning chunk-based visuomotor policies for long-horizon robot manipulation remains challenging. Recent action-chunking methods have shown promising pe

Understanding the Limits of Agentic ICD Coding

arXiv:2609.13806v1 Announce Type: cross Abstract: ICD-10-CM codes are alphanumeric codes used in the US to classify diagnoses and injuries for medical billing and epidemiological reporting. Standard I

agentsarxiv-cs-ai

Tutorials

Understanding User Preferences of a Slope-Aware Variable-Admittance Filter for a Robot Guide Dog

arXiv:2609.15362v1 Announce Type: new Abstract: This letter investigates how the parameters of a slope-aware variable-admittance filter influence user preferences in force-based interaction with a rob

tutorialsarxiv-cs-ro

Unfair Utilities and First Steps Towards Improving Them

arXiv:2306.00636v3 Announce Type: replace-cross Abstract: Many fairness criteria constrain the policy or choice of predictors, which can have unwanted consequences, in particular, when optimizing the

safetyarxiv-cs-lg

UniCAR-RL: Seeing Better before Thinking Deeper in Visual Mathematics

arXiv:2609.13849v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) often struggle with complex mathematical visual reasoning primarily due to a lack of fine-grained perception, c

Applications

UniE2F: A Unified Diffusion Framework for Event-to-Frame Reconstruction with Video Foundation Models

arXiv:2602.19202v3 Announce Type: replace Abstract: Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity

applicationsarxiv-cs-cv

UniqueShip: Mitigating Data Leakage in Acoustic Ship Classification Benchmark Datasets

arXiv:2609.13659v1 Announce Type: cross Abstract: Underwater Acoustic Target Recognition (UATR) of ships is well-suited for machine learning, yet its progress is hindered by the lack of large, diverse

Universal Topological Regularity of Syntactic Structures

arXiv:2302.00129v2 Announce Type: replace Abstract: Despite their widespread use, the principles governing the organisation of syntactic dependency trees remain poorly understood. I analyse dependency

researcharxiv-cs-cl

Unlabeled Multi-Robot Motion Planning with Improved Separation Trade-offs

arXiv:2603.19502v2 Announce Type: replace-cross Abstract: We study unlabeled MRMP for unit-disk robots in a polygonal environment. Although the problem is hard in general, polynomial-time solutions ex

researcharxiv-cs-ro

Unlocking the Unsolvable: Teacher-Guided Curriculum for Data-Efficient RLVR

model-releasesarxiv-cs-cl

arXiv:2609.13997v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has shown remarkable success in improving the mathematical reasoning of large language models. Yet

Unraveling the iterative CHAD

arXiv:2505.15002v3 Announce Type: replace-cross Abstract: Combinatory Homomorphic Automatic Differentiation (CHAD) was originally formulated as a semantics-driven source-to-source transformation for r

Unsupervised Clustering for Fault Analysis in High-Voltage Power Systems Using Voltage and Current Signals

arXiv:2505.17763v2 Announce Type: replace Abstract: The widespread use of sensors in modern power grids has led to the accumulation of large amounts of voltage and current waveform data, especially du

safetyarxiv-cs-lg

Local Ai

Unsupervised Keypoints for Real-Time Fall Detection: Comparative Analysis Under Real-world Conditions with Predictive Bandwidth Reduction

arXiv:2607.15400v3 Announce Type: replace Abstract: Falls among older adults are a major safety and health-systems challenge, yet continuous in-person monitoring is difficult to sustain across home an

local-aiarxiv-cs-cv

Unsupervised Point Cloud Registration via Training-Time Semantic Guidance

arXiv:2609.15228v1 Announce Type: new Abstract: Unsupervised registration of large-scale LiDAR point clouds remains challenging due to the geometric ambiguity inherent in outdoor scenes, which degrade

URCHIN: A Horizontal Spiking Language Model for Data-Constrained Pretraining

model-releasesarxiv-cs-cl

arXiv:2609.13899v1 Announce Type: cross Abstract: The BabyLM challenge measures how much language a model can learn from developmentally-plausible, child-scale data rather than internet-scale corpora,

Utility-Guided Agent Orchestration for Efficient LLM Tool Use

arXiv:2603.19896v2 Announce Type: replace Abstract: Tool-using large language model (LLM) agents often face a fundamental tension between answer quality and execution cost. Fixed workflows are stable

V-ICAL Bench: Evaluating Video In-Context Learning for Multimodal Agents in Interactive Environments

arXiv:2609.15683v1 Announce Type: new Abstract: While In-Context Learning (ICL) enables models to adapt from exemplars without parameter updates, multimodal ICL remains largely underexplored, particul

Validating Hybrid-State Cache Recovery for GLM-5.3-Flash with vLLM and LMCache

arXiv:2609.15030v1 Announce Type: cross Abstract: External cache transfers can succeed while a hybrid language model resumes from an inconsistent state. We examine the full 45-layer GLM-5.3-Flash mode

Variational Template Matching with Statistical Fusion for Anomaly Detection in Patterned Structures

arXiv:2609.13298v1 Announce Type: cross Abstract: Anomaly detection in structured images is challenging in small-data settings where deep learning approaches are costly or impractical. Classical templ

Hardware

VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attention

arXiv:2609.15810v1 Announce Type: new Abstract: Diffusion Transformers deliver state-of-the-art video generation, but their long spatiotemporal sequences make attention the dominant deployment cost, a

hardwarearxiv-cs-cv

VectorHarness: Recovering Editable, Relation-Preserving Structure from Scientific Graphics

arXiv:2609.13294v1 Announce Type: new Abstract: Converting scientific graphics into editable representations remains a challenging problem for image-to-code generation because of their heterogeneous e

agentsarxiv-cs-cv