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Talk to Me, Jarvis: An Open-Source Edge-Deployable Voice Assistant Framework for Autonomous Racecars

arXiv:2609.21109v1 Announce Type: new Abstract: Recent advances in large language models have improved their effectiveness as back-end components for voice assistants, particularly in intent understan

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Human DGX agent

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Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue

DGX agent

arXiv:2609.21401v1 Announce Type: cross Abstract: Conversational AI systems produce fluent, socially appropriate responses, yet whether they participate in cooperative communication or merely simulate

safetyarxiv-cs-ai

21 Sept 2026

TALON: A Temporally Aware Longitudinal Framework for Radiology Report Generation

arXiv:2609.20826v1 Announce Type: new Abstract: Current radiology report generation (RRG) models usually produce descriptive reports based on a single examination or only the most recent prior examina

researcharxiv-cs-cl

Taming the Adversary: A Cost-to-Disturbance Ratio Approach to Adversarial Reinforcement Learning

arXiv:2603.12110v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) policies trained in simulation often degrade once deployed on real systems, where the controller must reject exter

TAPe+ML: A Compact Structured Representation for Multi-Task Computer Vision

arXiv:2609.20869v1 Announce Type: new Abstract: We present TAPe+ML v3, a compact computer vision system based on TAPe (Theory of Active Perception), a structured representation that encodes relations

researcharxiv-cs-cv

TatBLiMP: A Benchmark of Linguistic Minimal Pairs for Tatar

model-releasesarxiv-cs-cl

arXiv:2609.20832v1 Announce Type: new Abstract: We introduce TatBLiMP, the first benchmark of linguistic minimal pairs for Tatar (tt, ISO 639-3 tat), a Qypchaq Turkic language written in Cyrillic. To

TERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor

arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-contro

local-aiarxiv-cs-ai

The Communication Bottleneck: A Round-Trip Study of Tree-Structured Expression Serialization in Language Models

arXiv:2609.21509v1 Announce Type: new Abstract: When language models reason in chain-of-thought or exchange free-text intermediates, they serialize structured information into natural language. How mu

The EventCV Library for Event-Based Robotic Vision

arXiv:2609.21330v1 Announce Type: new Abstract: Event cameras detect per-pixel brightness changes asynchronously on microsecond timescales, with high dynamic range and low power draw. These are desira

local-aiarxiv-cs-ro

The Hidden Cost of Digits: Number Normalization and WER in ASR Systems

arXiv:2609.21084v1 Announce Type: cross Abstract: Modern automatic speech recognition (ASR) systems trained on extremely large datasets can produce transcripts with numbers written in Arabic numerals.

researcharxiv-cs-cl

The Refutation Gap: Certifying Both Halves of an Optimality Claim

arXiv:2609.20873v1 Announce Type: cross Abstract: Synthesis pipelines increasingly claim not just that a program is correct, but that it is optimal. Such a claim has two halves with radically differen

The Role of Radiometric Features in Cross-Site Leaf-Wood Segmentation of LiDAR Point Clouds

arXiv:2609.21903v1 Announce Type: new Abstract: Leaf-wood segmentation of individual trees from LiDAR point clouds is essential for quantitative structure models (QSMs) used in non-destructive biomass

researcharxiv-cs-cv

The Spoken Wikipedia Presentation Corpus

arXiv:2609.21676v1 Announce Type: cross Abstract: We present the Spoken Wikipedia Presentation Corpus, an extension of the Spoken Wikipedia Corpora featuring LLM-generated slide decks for multimodal A

researcharxiv-cs-cl

The Stochastic Shift: A New Evaluation Paradigm for Text-to-SQL with AI Operators

arXiv:2609.21133v1 Announce Type: cross Abstract: SQL has been augmented with AI operators, enabling modern data analytics platforms to derive insights from both structured and unstructured data. We o

researcharxiv-cs-ai

The Weight Is Over - Interactive Diffusion on Consumer GPUs

arXiv:2609.21849v1 Announce Type: cross Abstract: On-device inference is booming, but the momentum is almost all in language models. Diffusion pipelines are memory hungry, latency-sensitive, and requi

local-aiarxiv-cs-cv

Think Locally, Refine Globally for Memory-Efficient 3D Reconstruction

arXiv:2609.21437v1 Announce Type: cross Abstract: We propose LoG-VGGT, a memory-efficient framework for long-sequence 3D reconstruction that balances local temporal modeling with global camera consist

researcharxiv-cs-ai

TierKV: Long-Context On-Device LLMs via Predictive Multi-Tier KV Caching

arXiv:2609.21172v1 Announce Type: new Abstract: Large language models (LLMs) are moving onto mobile devices for increasingly diverse workloads over text, images, video, and audio. These applications o

local-aiarxiv-cs-lg

Tilt as a Certified Resource: Preserving Motor Wrench-Rate Authority on Articulated Multirotors

arXiv:2609.21580v1 Announce Type: new Abstract: Fully-actuated multirotor aerial vehicles must not only track nominal wrenches but retain the 'readiness' to modulate them rapidly under disturbances. C

safetyarxiv-cs-ro

Time series generation with spectrally aligned latent flow matching

arXiv:2609.21989v1 Announce Type: new Abstract: Latent flow models have proven to be a reliable and cost-effective method for time series generation. However, the latent compression induces unwanted a

TinyCeNN-LM: Quality-Gated Conversion of Pretrained Attention with CeNN-Inspired Cellular-Recurrent Layers

arXiv:2609.21139v1 Announce Type: new Abstract: Replacing attention in a pretrained language model is a compatibility problem: a plausible substitute may alter representations expected by later layers

Touvigation: Embodied Adaptive Object Acquisition for Blind and Low-Vision Users in Unfamiliar Indoor Environments

arXiv:2609.21828v1 Announce Type: cross Abstract: Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-lan

local-aiarxiv-cs-ai

Toward individual-level calibration in affect recognition with perceptual adjustment queries

arXiv:2609.21073v1 Announce Type: new Abstract: Behavioral tasks measuring facial affect perception assume that identical stimuli impose equivalent perceptual difficulty across participants. However,

Towards Effective Visual-Inertial SLAM with Passive-Only Sensors for Low-Cost Autonomous Underwater Vehicles

model-releasesarxiv-cs-ro

arXiv:2609.21015v1 Announce Type: new Abstract: Improvements to Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) for low-cost autonomous underwater vehicles (AUVs) are critical for tran

Towards Fine-Grained Object Manipulation: SAM3-Guided Visuomotor Policy with Persistent Memory Learning and Focused Visual Conditioning

arXiv:2609.21621v1 Announce Type: new Abstract: Fine-grained object (FO) manipulation requires robots to distinguish a specified FO from visually similar objects and execute actions reliably despite s

safetyarxiv-cs-ro

Towards Secure Cloud-Native Computing: Unveiling Kubernetes Misconfigurations with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.20834v1 Announce Type: new Abstract: In the rapidly evolving landscape of cloud-native computing, Organizations are increasingly adopting infrastructure models that emphasize scalability, f

Towards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation

arXiv:2603.16086v2 Announce Type: replace-cross Abstract: While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts o

Tutorials

TRACE: Coverage Path Planning for Unknown Environments Using Hierarchical Coverage Tree

arXiv:2609.21777v1 Announce Type: new Abstract: This paper presents a novel online coverage path planning (CPP) algorithm, called TRACE, for real-time coverage of unknown environments. TRACE is built

tutorialsarxiv-cs-ro

Tracing the Evidence Behind Zero-Shot Time-Series Forecasting: A Source-First Taxonomy and Audit Framework

arXiv:2609.21425v1 Announce Type: new Abstract: Zero-shot time-series forecasting (TSF) is often described as forecasting without target-specific parameter updates, but that training-status condition

Trading Depth for Time in Recurrent Transformers

arXiv:2609.21605v1 Announce Type: new Abstract: Recurrent Transformers increase computational depth through temporal recurrence, feeding each token's high-level hidden state into the computation of th

Traffic Sign Recognition for Autonomous Driving Using Branched YOLOv2 and Geometric Features

arXiv:2609.22060v1 Announce Type: new Abstract: Traffic sign recognition (TSR) is an important perception task for autonomous driving and advanced driver-assistance systems, where a system must both l

local-aiarxiv-cs-cv

Trajectory Entropy Reinforcement Learning for Robust Robot Motor Skill Learning

arXiv:2505.04193v2 Announce Type: replace Abstract: Simplicity is a critical inductive bias for designing data-driven controllers, especially when robustness is important. Despite the impressive resul

safetyarxiv-cs-lg

Transferable knowledge graphs with executable learned operators for algorithm design

arXiv:2603.27922v2 Announce Type: replace Abstract: Procedural knowledge in algorithm design is embedded in source code and rebuilt for each new domain. We introduce Generative Executable Algorithm Kn

local-aiarxiv-cs-ai

Transformers Discover Molecular Structure Without Graph Priors

arXiv:2510.02259v2 Announce Type: replace Abstract: Computational simulations play a central role in scientific discovery, and machine learning (ML) has emerged as a promising alternative to tradition

local-aiarxiv-cs-lg

Transsion's Speaker-Attributed Multilingual ASR System for the MLC-SLM 2026 Challenge

arXiv:2609.20833v1 Announce Type: new Abstract: This paper presents the Transsion Speech Team submission to Task 1 of the MLC-SLM 2026 Challenge, which focuses on speaker-attributed transcription for

local-aiarxiv-cs-cl

TrialAtlas: Multi-Agent Research Organization for Clinical Trial Design and Optimization

model-releasesarxiv-cs-cl

arXiv:2609.21859v1 Announce Type: new Abstract: Nearly 90% of drugs entering clinical development ultimately fail, despite billions of dollars in investment. Pharmaceutical companies therefore rely on

Triply-Scalable Equivariant Gaussian Process Modeling

arXiv:2609.21085v1 Announce Type: cross Abstract: Gaussian processes (GPs) provide principled probabilistic predictions while encoding prior knowledge, including equivariances. Yet, their use in large

Trustworthy FinAInce: Unpacking How AI-Mediated Financial Advice is Judged

arXiv:2609.20989v1 Announce Type: cross Abstract: As generative AI is increasingly used as a source of personal financial guidance, understanding how people appraise such advice is important for suppo

safetyarxiv-cs-ai

TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching

arXiv:2607.16894v2 Announce Type: replace Abstract: Many complex systems, including brain networks, financial markets, and gene-regulatory circuits, are better described by interaction structures that

ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation

arXiv:2603.03279v2 Announce Type: replace-cross Abstract: Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing

safetyarxiv-cs-cv

Uncertainty-driven training for three-dimensional calibrated lung nodule classification

model-releasesarxiv-cs-cv

arXiv:2609.20905v1 Announce Type: cross Abstract: In this work, we present an uncertainty-driven training framework for three-dimensional computed tomography (CT) lung nodule classification, where val

Understanding Engagement and Intrusiveness in Assistive Human-Robot Interaction Using Individual Traits

arXiv:2609.21744v1 Announce Type: new Abstract: Robot assistance is particularly crucial in unfamiliar tasks, where users must understand task requirements while coordinating with the robot. Previous

researcharxiv-cs-ro

Understanding In-context Learning of Addition via Activation Subspaces

arXiv:2505.05145v4 Announce Type: replace-cross Abstract: To perform few-shot learning, language models extract signals from a few input-label pairs, aggregate them into a learned prediction rule, and

Understanding LLM Quantization through Activation-Guided Compensation and Orthogonal Residuals

arXiv:2609.21450v1 Announce Type: new Abstract: Post-training weight-activation quantization reduces the memory and inference costs of large language models, but aggressive W4A4 quantization remains d

Understanding Structural Representation in Foundation Models for Polymers

arXiv:2512.11881v2 Announce Type: replace-cross Abstract: From the relative scarcity of training data to the lack of standardized benchmarks, the creation of effective foundation models for polymers f

Uni-PrevPredMap: Extending PrevPredMap to a Unified Framework of Prior-Informed Modeling for Online Vectorized HD Map Construction

arXiv:2504.06647v4 Announce Type: replace Abstract: Safety-critical autonomous driving motivates the effective use of prior information. For online vectorized HD map construction, temporal predictions

safetyarxiv-cs-cv

Agents

Value-Sensitive Delegation in Everyday AI Agent Use: Evidence from OpenClaw

arXiv:2609.22067v1 Announce Type: cross Abstract: Users increasingly delegate work to autonomous AI agents, yet evaluations typically measure task completion rather than the values users prioritize. U

agentsarxiv-cs-ai

Agents

VeriFuse: Bounded Vision-Language Arbitration and Reason-Guided Refinement for Cooperative 3D Perception

arXiv:2609.21323v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong scene understanding and semantic judgment across diverse tasks, but their appropriate role in coo

agentsarxiv-cs-cv

Hardware

Verify, Don't Trust: Agentic Model Development for Video Discovery Retrieval at Scale

arXiv:2609.21257v1 Announce Type: cross Abstract: Large language model (LLM) agents can propose, implement, and evaluate model changes. Autoresearch loops demonstrate this capability through minutes-s

hardwarearxiv-cs-ai