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StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras

arXiv:2610.12734v1 Announce Type: cross Abstract: Stereo vision is increasingly used for robotic manipulation, with a growing body of work incorporating it into Vision-Language-Action (VLA) models. Ho

safetyarxiv-cs-lg

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Structural and Representational Agency in LLM-Driven Timbre Generation and Interpolation

DGX agent

arXiv:2610.12532v1 Announce Type: cross Abstract: Generative creative interfaces routinely report the user's position within a space of possibilities. Such displays imply that the quantities shown wer

researcharxiv-cs-lg

12 Oct 2026

Local Ai

Structural Automata for Neural Semantic Parsing

arXiv:2610.13896v1 Announce Type: new Abstract: Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfo

local-aiarxiv-cs-cl

Structure-Aware Numerical Stabilization for Half-Precision Proximal Policy Optimization

arXiv:2610.13306v1 Announce Type: new Abstract: Local online training on resource-constrained platforms requires low computational and training-state overhead. We study the numerical stability and com

Studying Comics at Scale with Artificial Intelligence: The PAGE Framework and Three Studies of American Comics and Japanese Manga

arXiv:2610.13840v1 Announce Type: new Abstract: Comics are one of the great visual records of the twentieth century: hundreds of thousands of pages in which a mass readership saw its leaders, its wars

Applications

Studying the Effects of Task Diversity Using Small Mathematical Worlds

arXiv:2610.13750v1 Announce Type: new Abstract: Basic mathematical tasks like modular addition have been a valuable tool for illuminating aspects of neural network behavior that are challenging to see

applicationsarxiv-cs-lg

Surfing the Activation Wave: Analyzing the Information and Geometry of LLM Hidden States for Speculative Decoding

arXiv:2610.12939v1 Announce Type: cross Abstract: Decoder hidden states from different layers of large language models (LLMs) often encode complementary information. However, existing speculative deco

safetyarxiv-cs-ai

Surrogate Graph Partitioning for Spatial Prediction

arXiv:2510.07832v2 Announce Type: replace-cross Abstract: Spatial prediction refers to the estimation of unobserved values from spatially distributed observations. Although recent advances have improv

Sustainable Cloud-Fog-Edge Systems for Smart Buildings: Algorithmic Adaptation under Memory Constraints and Dynamic Orchestration Strategies

arXiv:2610.13307v1 Announce Type: new Abstract: The escalating environmental footprint of the Information and Communication Technol- ogy (ICT) sectorwith global Data Center electric- ity usage potenti

agentsarxiv-cs-lg

SWE-Critix: Post-Training Generalist Verifiers for Assessing Coding-Agent Trajectories

arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c

agentsarxiv-cs-ai

SWE-DeceptionBench: Benchmarking Deceptive Behaviors of LLMs Across the Software Development Lifecycle

model-releasesarxiv-cs-ai

arXiv:2610.13626v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used throughout the software development lifecycle. This growing reliance on LLMs raises concerns about

SWE-Duel: Towards a Self-Scaling Arena for Coding Agents

model-releasesarxiv-cs-cl

arXiv:2610.12569v1 Announce Type: new Abstract: Static coding benchmarks are fixed at release. Over time their tasks leak into training data, and stronger agents eventually saturate them. We argue tha

SWEAR: Section-Wise Efficient Audio Reasoning via Self-Rated Difficulty

arXiv:2610.13081v1 Announce Type: new Abstract: Recent work on large audio-language models (LALMs) explores adaptive reasoning to balance accuracy and efficiency. However, existing approaches often re

SynAct: Synergistic Active Feedback Learning for LLM Agents

arXiv:2610.12651v1 Announce Type: new Abstract: LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge

agentsarxiv-cs-lg

TabMF: Learning Dataset Representations with Tabular Foundation Models

arXiv:2610.13818v1 Announce Type: new Abstract: Representations of supervised datasets support higher-level machine-learning tasks such as dataset retrieval and distribution-shift monitoring. However,

TabReliBench: Evaluating Tabular Foundation Models Beyond Predictive Accuracy

arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions

Hardware

Tabular Foundation Models Are Effectively Shallow

arXiv:2610.13253v1 Announce Type: cross Abstract: In-context-learning Tabular Foundation Models (TFMs) are uniquely suited to scenarios with limited resources or privacy constraints, as they solve new

hardwarearxiv-cs-ai

Tactile Sensing-based Secure and Gentle Grasping of Unknown Objects

arXiv:2610.12790v1 Announce Type: new Abstract: Reliable robotic manipulation requires maintaining a firm grasp while strictly avoiding both contact slip and structural damage to the object. Satisfyin

researcharxiv-cs-ro

Taking Tokenization off the Host for Agentic LLM Serving

model-releasesarxiv-cs-cl

arXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still

TAME-Nav: Temporal Asymmetric Mixture-of-Experts Distillation for Agile and Versatile Robot Navigation

arXiv:2610.12877v1 Announce Type: new Abstract: Agile and reliable navigation is a core capability for embodied robots navigating complex spatial constraints and dynamic interactions. However, a singl

safetyarxiv-cs-ro

Target-Constrained Pooling for Trajectory Extrapolation

arXiv:2610.13034v1 Announce Type: new Abstract: Trajectory extrapolation from a partial target trajectory is underdetermined, but completed related trajectories provide information about the unresolve

Task Context Shapes Component Roles in Language Models

model-releasesarxiv-cs-ai

arXiv:2610.13895v1 Announce Type: cross Abstract: Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in eac

Teaching neural decoders with language

arXiv:2610.12921v1 Announce Type: new Abstract: Brain-computer interfaces decode neural activity, yet class-label supervision (CLS) leaves relationships among classes implicit. We propose Language as

TelcoAgent: A Scalable 5G Multi-KPM Forecasting With 3GPP-Grounded Explainability

arXiv:2606.19821v2 Announce Type: replace Abstract: Key Performance Measurement (KPM) forecasting is essential for proactive network management of 5G and next-generation telecom networks. However, exi

agentsarxiv-cs-ai

Temporal Evidence Forests for Long-Horizon Multi-Party Conversational Memory

model-releasesarxiv-cs-cl

arXiv:2610.12874v1 Announce Type: new Abstract: Long-term memory has been widely adopted in LLM-based agents to support persistent interaction and personalized assistance. Long-term multi-party intera

Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels

arXiv:2610.13221v1 Announce Type: new Abstract: Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets

TernaryLLM: Ternarized Large Language Model

arXiv:2406.07177v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on Natural Language Processing (NLP) tasks, but they are hindered by high computat

Test-Time Memory Construction

arXiv:2610.13348v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to answer questions over long interaction histories, where relevant evidence may be scattered across distant sessi

The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs

arXiv:2510.13154v3 Announce Type: replace Abstract: What happens inside a language model when alignment training conflicts with a cultural value it encodes? Across 16 MENA countries, 26 models, and 1.

safetyarxiv-cs-cl

The Evidence Anchoring Boundary: Where Visual Interventions Matter and When They Help in Multimodal LLMs

arXiv:2610.12981v1 Announce Type: cross Abstract: Visual interventions provide a training-free way to reduce hallucinations in multimodal large language models. However, an intervention may have littl

The Expressive Power of Random-Feature MPNNs Across Graph Sizes

arXiv:2610.12809v1 Announce Type: new Abstract: Continuous random node features increase the expressivity of message-passing neural networks (MPNNs), but existing theoretical analyses are not fine-gra

Tutorials

The Limits of Query Monitoring against Distributed Model Extraction

arXiv:2610.13083v1 Announce Type: cross Abstract: Model providers now face distillation campaigns run through thousands of accounts, each of which looks like an ordinary user. When network and payment

tutorialsarxiv-cs-lg

The Predictability Bias of Joint-Embedding Predictive Learning in Medical Imaging

arXiv:2610.13237v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) learn by predicting teacher representations of masked regions from visible context. Point prediction

safetyarxiv-cs-lg

The value of information and the emergence of communication in evolved e-puck robots

arXiv:2610.13118v1 Announce Type: new Abstract: We study when communication emerges between autonomous agents and what role an innate action selection architecture plays. Two e-puck robots, reconstruc

agentsarxiv-cs-ro

Time Delay System for Sequence Modeling

arXiv:2610.12864v1 Announce Type: new Abstract: Existing sequence models share a critical limitation: they lack an explicit, interpretable mechanism for content-aware temporal recall. LSTMs compress e

Toward Maximizing Algebraic Connectivity via Density-Dependent Backbone Construction and Reinforcement Learning Completion

arXiv:2610.12697v1 Announce Type: cross Abstract: This paper studies an open network design problem of constructing graph topologies with maximum algebraic connectivity under fixed numbers of vertices

Towards a Measure Theory of Semantic Information

arXiv:2508.00525v2 Announce Type: replace-cross Abstract: A classic account of the quantification of semantic information is that of Bar-Hiller and Carnap. Their account proposes an inverse relation b

Towards a Unified Taxonomy of Agricultural Harvesting Technologies: Linking Physical Interaction, Automation, and Selectivity

arXiv:2610.13688v1 Announce Type: new Abstract: Harvesting technologies have evolved from conventional mechanized systems based on bulk mechanical interaction toward increasingly automated and robotic

researcharxiv-cs-ro

Towards Defining, Measuring, and Leveraging Creativity in AI Applications

arXiv:2610.12845v1 Announce Type: new Abstract: Despite extensive research, computational creativity still lacks a conceptually grounded, practically relevant, and empirically applicable formal defini

Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf

arXiv:2610.13036v1 Announce Type: new Abstract: Evaluating deep learning optimizer is challenging because confounding factors such as hyperparameter tuning and optimizer-model co-design often obscure

Towards Enriching Design-Time Models with Evidence from Simulation and Operational Activities

arXiv:2610.13456v1 Announce Type: new Abstract: Cyber-Physical Systems are developed through multiple model based activities, comprising several stages of development. As the development progresses th

Towards Safer Cities: A Design Process for Perception Datasets in Urban Driving Scenarios

arXiv:2610.13077v1 Announce Type: new Abstract: Urban environments present significant challenges for the perception systems of automated driving due to their high complexity, characterized by dense t

researcharxiv-cs-ro

Towards the Roof of the World: NLP Progress in Tibetan Languages

arXiv:2610.13398v1 Announce Type: new Abstract: Tibetan, spoken by some seven million people on and around the Qinghai-Xizang Plateau, remains underrepresented in natural language processing (NLP). We

Towards Understanding the Training of GFlowNets: A Theoretical Perspective

arXiv:2610.13711v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) learn policies that sample discrete objects in proportion to a positive reward. They are trained by minimizing bala

safetyarxiv-cs-lg

Tracing and Taming Hallucinated Terms via Subsequence-Association Filtering and Breadth-Aware Selection for LLM Query Expansion

arXiv:2610.13810v1 Announce Type: cross Abstract: Large language models (LLMs) are now a standard source of query expansion terms but they hallucinate. They inject non existent entities and off-topic

safetyarxiv-cs-cl

Tracking the Invisible: Self-Supervised Wheel Track Detection with Thermal-RGB Fusion

arXiv:2610.13872v1 Announce Type: cross Abstract: Accurate detection of drivable area is essential for autonomous driving and advanced driver assistance systems. While state-of-the-art methods focus o

safetyarxiv-cs-ro

Trainable Quantum-Native Language Models: Dissipative Memory, Capacity Limits, and Hardware Validation

arXiv:2610.12806v1 Announce Type: cross Abstract: We study byte-level autoregressive language models whose hidden state is a small quantum register, whose transitions are learned token-conditioned qua

Training User Simulators with Latent Intrinsic Feedback

arXiv:2610.13617v1 Announce Type: new Abstract: User simulators are gaining attention as environments to train LLM assistants that can better cope with the nuances of multi-turn conversations with rea