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The AR Fairness Metamodel: A Structured Framework for Fairness Measures

arXiv:2609.19234v1 Announce Type: cross Abstract: This paper presents the AR fairness metamodel, a framework designed to represent, analyze, and compare different fairness scenarios. The metamodel con

safetyarxiv-cs-ai

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The Bias of Nonlinear Two-Time-scale Stochastic Approximation under Constant Step-Sizes

DGX agent

arXiv:2609.20409v1 Announce Type: new Abstract: Two-timescale stochastic approximation (TTSA) is a fundamental tool for analyzing coupled iterative algorithms in reinforcement learning, optimization,

safetyarxiv-cs-lg

18 Sept 2026

The Complexity Kink: A Prompt-Side Structural Complexity Index for Code-Generation Reliability

arXiv:2609.19616v1 Announce Type: new Abstract: Complexity measured from generated code is failure-dependent: a difficult prompt can yield a short failing program and be assigned low output complexity

The Environmental Impacts of Language Model Training Keep Rising Now is the Time to Catch Impacts on the Rebound

arXiv:2510.09022v2 Announce Type: replace Abstract: Recent Machine Learning (ML) approaches have shown increased performance on benchmarks at the cost of escalating compute demands. Hardware, algorith

The First-Order Oracle Complexity of Lipschitz Convex Optimization in Nondual Settings

arXiv:2609.20687v1 Announce Type: cross Abstract: We study first-order black-box convex optimization over an ell_p-ball for objectives Lipschitz in the ell_q-norm, solving in the affirmative the nonsm

Tutorials

The Life of a Token: from Words to Bits on the Wire

arXiv:2609.19924v1 Announce Type: cross Abstract: Large Language Models (LLMs) transform vast collections of unstructured text into semantic patterns used for language generation and reasoning tasks.

tutorialsarxiv-cs-lg

The Missing Complement: State-Conditioned Minimal Sufficient Evidence for Coding Agents

arXiv:2609.20050v1 Announce Type: cross Abstract: A coding agent halfway through an issue has already read much of what a retriever ranks highest. Relevance is scored per passage, but sufficiency belo

The Neutral Mask: How Alignment Training Provides Shallow Alignment while Leaving Partisan Structure Intact in a Large Language Model

arXiv:2606.09735v2 Announce Type: replace Abstract: The ambition behind alignment training is to make large language models safe and useful. The primary mechanisms, reinforcement learning from human f

The Organization of Inference: Information, Resource Constraints, and AI Production

arXiv:2609.20449v1 Announce Type: new Abstract: The economic value of inference depends on how capacity and task information are distributed across stages of AI production. We study these organization

applicationsarxiv-cs-ai

Hardware

The Output-Space Hypothesis: Enumerative Equivalence Checking for Tensor Programs

arXiv:2609.19611v1 Announce Type: cross Abstract: Tensor programs, as used in deep learning models, are a prime target for optimization, as small performance improvements can have a large impact acros

hardwarearxiv-cs-lg

The Public Discourse Corpus (PDC): A Speaker-Attributed Dataset for Valence and Epistemic Modality with Target Speaker Participation

arXiv:2609.20232v1 Announce Type: new Abstract: We introduce the extbf{Public Discourse Corpus (PDC)}, the first dataset of public-figure interview speech jointly annotated for affective valence and e

The Role of Fine-grained Harm Signals in LLM Safety

arXiv:2609.19366v1 Announce Type: new Abstract: Prior work has shown that internal harmfulness representations in large language models vary across risk categories, while sharing a common general harm

safetyarxiv-cs-cl

The segmentation ceiling: why explicit left-ventricular masks do not improve learned ejection-fraction regression

arXiv:2609.19730v1 Announce Type: cross Abstract: Accurate estimation of left ventricular ejection fraction (EF) from echocardiography is central to cardiovascular care, and deep learning enables auto

researcharxiv-cs-cv

The syntax and semantics of goals

arXiv:2609.19448v1 Announce Type: new Abstract: In both cognitive science and computer science, goals are conceptualized as cognitive states that flexibly combine with world knowledge to organize and

researcharxiv-cs-ai

Think Thrice Before Reranking: Multi-perspective Evidence and Reasoning Integration for Text Reranking

arXiv:2609.20131v1 Announce Type: cross Abstract: Reasoning-based reranking with Large Language Models (LLMs) has shown promising improvements in text ranking. However, current methods predominantly r

safetyarxiv-cs-cl

Time-Efficient Iterative Learning Planning for Safety-Critical Dynamic Obstacle Avoidance

arXiv:2609.20435v1 Announce Type: new Abstract: Autonomous mobile robots require timeefficient planning and safety-critical dynamic obstacle avoidance under constrained onboard computation. While Iter

TinyCNN: A 193K-Parameter Network for On-Device Plant Disease Detection, with a Cross-Dataset Robustness Diagnosis

model-releasesarxiv-cs-cv

arXiv:2609.20290v1 Announce Type: new Abstract: Detecting crop disease early is central to sustainable agriculture and food security under United Nations Sustainable Development Goal 2 (Zero Hunger),

To Copy or Not to Copy: Controlling Speculative Decoding via Intrinsic Model Signals

arXiv:2609.20186v1 Announce Type: new Abstract: Speculative Decoding (SD) has significantly accelerated Large Language Model (LLM) inference, yet existing approaches face a fundamental tradeoff betwee

To Memories and Beyond: From Remembering to Knowing You across Long-Term Multimodal Personal Archives

arXiv:2609.19167v1 Announce Type: new Abstract: As AI systems evolve into personalized digital companions, a central capability is reasoning over a user's long-term personal history: not merely storin

TorchCraft: Unified binder design by inverting an all-atom structure predictor

arXiv:2609.19770v1 Announce Type: new Abstract: All-atom structure predictors model diverse molecular interactions, but using their learned structural priors for binder design remains challenging. Her

researcharxiv-cs-ai

TouchSight: Bare-Handed Tactile Prediction from Egocentric Video via Generative Visual Augmentation

arXiv:2609.20414v1 Announce Type: cross Abstract: Tactile signals provide direct contact and force measurements that are essential for understanding physical interactions and enabling dexterous roboti

applicationsarxiv-cs-ai

Towards a Unified Modality-Agnostic Multimodal Framework for Cognitive Workload Assessment

arXiv:2609.20199v1 Announce Type: new Abstract: Cognitive workload reflects the mental effort required during task performance and is central to the design of adaptive human-machine systems. The use o

Local Ai

Towards Active Cross-View Object Geo-Localization

arXiv:2609.19662v1 Announce Type: new Abstract: Cross-view object geo-localization (CVOGL) typically assumes a fixed query image, overlooking the ability of mobile agents to actively acquire more info

local-aiarxiv-cs-cv

Towards AI-enhanced control: a numerical technique for trajectory smoothing of a parallel robot for pancreatic surgery

model-releasesarxiv-cs-ro

arXiv:2609.20499v1 Announce Type: new Abstract: The paper presents a numerical approach for the end-effector trajectory smoothing of a parallel robot designed for minimally invasive pancreatic surgery

Towards High-DoF Dexterous Manipulation through VLA Post-Training

arXiv:2609.19666v1 Announce Type: new Abstract: Imitation-learned vision--language--action (VLA) foundation models acquire broad manipulation capabilities by scaling robot data across tasks and embodi

Towards Proactive Detection of User-Side Implicit Conflicts in Human-LLM Dialogue

arXiv:2609.19155v1 Announce Type: new Abstract: In Human-LLM dialogue, follow-up user utterances may implicitly conflict with earlier intents, leading the LLM to misinterpret user needs and generate i

Towards Scaling Marine Perception with Synthetic Data

arXiv:2609.20680v1 Announce Type: cross Abstract: Scalable machine learning in challenging underwater environments is strongly limited by the lack of labeled real-world training data. This data is oft

applicationsarxiv-cs-cv

TRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives

arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genre

TraceFlow: Guiding Frozen Flow-Matching Robot Policies with Success and Failure Traces

arXiv:2609.20646v1 Announce Type: new Abstract: A vision-language-action (VLA) policy with a flow-matching action expert generates each action chunk (a short command sequence) by integrating a learned

Tutorials

Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks

arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a

tutorialsarxiv-cs-lg

Training Neural Networks to Approach the Optimum Bayes Estimator in Dense Multi-Emitter Localization

arXiv:2609.20465v1 Announce Type: new Abstract: We train neural networks on synthesized frames to approach the optimum Bayes estimator for dense emitter localization. The result justifies the future w

Transformer fault diagnosis using an efficient simulation-driven variational quantum classifier with domain-aware feature encoding

model-releasesarxiv-cs-lg

arXiv:2609.20214v1 Announce Type: cross Abstract: Early transformer fault diagnosis is challenged by nonlinear dissolved-gas interactions, overlapping fault signatures, and limited labeled data, while

TripScore: Aligning LLMs for Real-World Travel Planning via Expert-Calibrated Reward

arXiv:2510.09011v4 Announce Type: replace Abstract: In our deployed travel-planning service, most users give minimal inputs or free-form requests rather than the structured constraint checklists assum

Tutorials

Truncated automatic sparse differentiation for machine learning interatomic potentials

arXiv:2609.20510v1 Announce Type: cross Abstract: Machine learning interatomic potentials (MLIPs) learn the mapping from atomic positions to potential energy. The forces, the negative gradient of this

tutorialsarxiv-cs-lg

Trust, but Validate the Instrument: Auditing AI-Generated RTL Verification Plans on Authored Security-Regression Proxies

arXiv:2609.19844v1 Announce Type: cross Abstract: AI-generated RTL verification plans can satisfy a provider schema yet fail at the boundary to trusted execution. We present SecTB-RTL, an auditable fr

ULOHA: An Underwater Bimanual Robot System for Robot Learning

arXiv:2609.19200v1 Announce Type: new Abstract: Underwater visuomotor policy learning has focused primarily on single manipulators, while bimanual imitation learning has been studied largely in air. W

Local Ai

Understanding and Exploiting Diagonal Attention Sparsity in Autoregressive Image Generation

arXiv:2609.19702v1 Announce Type: new Abstract: Autoregressive image generation has emerged as a paradigm for multimodal AI systems due to its compatibility with transformer-based LLM serving infrastr

local-aiarxiv-cs-cv

Understanding Role Switching in Human-AI Collaboration through Multimodal Behavioral Signals

arXiv:2509.20666v2 Announce Type: replace-cross Abstract: Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which sub

researcharxiv-cs-ai

Agents

Underwater Visual Target Tracking with Target-Specific Depth Estimation and Adaptive Model-Fusion Predictive Control

arXiv:2609.20731v1 Announce Type: new Abstract: Vision-based underwater target tracking is challenged by unreliable depth measurements and unknown target motion. This paper proposes a stereo visual-se

agentsarxiv-cs-ro

Uni-LaDiR: Latent Diffusion Unifies Multimodal Reasoning

arXiv:2609.19878v1 Announce Type: cross Abstract: Multimodal reasoning requires models to draw on information from multiple modalities throughout the reasoning process. Yet existing methods often conc

researcharxiv-cs-cl

UniExo: Unified Multi-Skill Policies for Musculoskeletal Locomotion and Co-Adaptive Exoskeleton Control

arXiv:2609.19690v1 Announce Type: cross Abstract: Daily locomotion encompasses diverse activities and frequent transitions between them, yet most exoskeleton controllers are designed for a single acti

safetyarxiv-cs-lg

Agents

UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning

arXiv:2609.20089v1 Announce Type: new Abstract: Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing m

agentsarxiv-cs-ai

Unifying Models of Intergroup Hostility in Online Discourse

arXiv:2609.20808v1 Announce Type: new Abstract: Hostile rhetoric toward social groups can normalize exclusion and justify mistreatment, as well as contribute to rising polarization and political viole

applicationsarxiv-cs-cl

UniPolicy: Unified Objective-Specific Policies for Generative Search Advertising

arXiv:2609.20630v1 Announce Type: new Abstract: Search advertising connects user intent with commercial content and plays a critical role in platform monetization. Recent systems typically align pretr

Universal Navigation Interface: Robot-Free Data for Wheeled Robot Navigation

arXiv:2609.20114v1 Announce Type: new Abstract: Collecting real-world navigation data for mobile robots typically requires platform-specific teleoperation, making large-scale collection expensive and

applicationsarxiv-cs-ro

V2-STRep: VLM-Grounded Structured Task Representations for Reusable Robot Skills Acquired from Generated Videos

arXiv:2609.20582v1 Announce Type: new Abstract: Human manipulation videos provide rich motion and interaction cues for acquiring robot skills without robot demonstrations. Video generation models synt

applicationsarxiv-cs-ro

Local Ai

VABench: Measuring Embodied Spatial Intelligence through Visual Demonstrations, Active Perception, and Metric Control

arXiv:2609.19554v1 Announce Type: cross Abstract: Spatial intelligence requires more than describing object locations. Under incomplete observation, models must identify and acquire missing evidence,

local-aiarxiv-cs-cv

VakQA: A Benchmark and Evaluation Study for Telugu Spoken Factoid Question Answering

arXiv:2609.19879v1 Announce Type: new Abstract: Question answering has advanced rapidly with large language models, but predominantly for high-resource languages, in both text and spoken settings. Spo