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StreamTTO: Efficient Online Test-Time Optimization for Video Depth Completion

arXiv:2603.01765v5 Announce Type: replace Abstract: Monocular depth foundation models generalize across diverse scenes, but recovering accurate metric depth consistent with a target sensor remains cha

researcharxiv-cs-cv

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Structured Decomposition for Reliable LLM-Generated Access Control Policies

DGX agent

arXiv:2609.24036v1 Announce Type: new Abstract: This paper presents an LLM-based system that translates natural-language access control policies (NLACPs) into executable Rego code for Open Policy Agen

safetyarxiv-cs-ai

23 Sept 2026

STRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks

arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behavior

researcharxiv-cs-ai

SuperPCA: subspace analysis and an efficient algorithm for high-dimensional PCA

arXiv:2609.26406v1 Announce Type: cross Abstract: Principal component analysis (PCA) is a fundamental tool to reduce the dimensionality of the data in many applications. PCA finds a few signal directi

Syndrome, Synergy, and Safety: Structured Reasoning and Knowledge-Driven Alignment for TCM Prescription Generation

model-releasesarxiv-cs-cl

arXiv:2609.25755v1 Announce Type: new Abstract: Applying large language models to Traditional Chinese Medicine (TCM) prescription generation reveals three clinically critical gaps: models produce end-

Synthesis and editing of multi-instrument audio mixtures using scalar-quantised latents with MIDI Span conditioning

arXiv:2609.25546v1 Announce Type: cross Abstract: Music creation often involves iterative refinement, changing selected musical details while retaining the rest. To support such refinement, we introdu

Synthesizing Reactive Character Behaviors for Continuous Games via Programmatic Policy Search

arXiv:2609.24025v1 Announce Type: new Abstract: We present a method for synthesizing reactive character behaviors for continuous games as compact, human-readable programs. Game AI practice still relie

SyzHarness: Patch-Based Kernel Bug Reproduction with LLM-Synthesized Fuzzing Harnesses

arXiv:2609.23889v1 Announce Type: cross Abstract: Automated kernel vulnerability reproduction is essential for bug triage, patch validation, and regression testing, but still lacks an effective and ef

Local Ai

TailSpec-EASE: Knowledge-Graph-Regularized Linear Recommendation for Web Long-Tail Discovery

arXiv:2609.26143v1 Announce Type: cross Abstract: Recommender systems on Web platforms tend to over-serve popular items and neglect the long tail. Item-side knowledge graphs (KGs), often available as

local-aiarxiv-cs-lg

Local Ai

Taming CoT Obfuscation in VLMs: From Mechanistic Evidence to Activation Enforcement

arXiv:2609.24243v1 Announce Type: new Abstract: Reinforcement learning (RL) improves reasoning in vision-language models (VLMs) but can induce chain-of-thought (CoT) obfuscation: an operational, non-i

local-aiarxiv-cs-ai

Target alignment, dilution and forecast selection when cross-sectional forecasts share a common target

arXiv:2609.26303v1 Announce Type: cross Abstract: Forecasters often score the same units per date against one standardized realized outcome. We show that every standardized forecast splits exactly int

safetyarxiv-cs-lg

Targeted Review for AI-Assisted Biodiversity Surveys: Active Continuous-Score Occupancy Modeling

arXiv:2609.25657v1 Announce Type: new Abstract: We increasingly use machine learning to label scientific datasets. The models we develop and deploy are improving all the time, but they are not and wil

applicationsarxiv-cs-lg

Teaching Reinforcement Learning and Humanoid Robotics to High-School Students: An Expert-Validated Curriculum Design on a Low-Cost Open Platform

arXiv:2609.25674v1 Announce Type: new Abstract: Lower cost open source robots and reinforcement learning (RL) simulation tools create new opportunities for precollege students to engage with contempor

safetyarxiv-cs-ro

TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks

model-releasesarxiv-cs-cl

arXiv:2609.25356v1 Announce Type: new Abstract: Large language models (LLMs) offer great potential to automate a broad range of telecom engineering tasks by reasoning over standards, network configura

Tutorials

TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action

arXiv:2505.01583v2 Announce Type: replace Abstract: Understanding causal event relationships and achieving fine-grained temporal grounding in videos remain challenging for vision-language models (VLMs

tutorialsarxiv-cs-cv

Terminal Shrinkage Averaging Reveals a Schedule-Estimator Interaction in LLM Pretraining

model-releasesarxiv-cs-lg

arXiv:2609.25482v1 Announce Type: new Abstract: Large language model (LLM) pretraining conventionally returns the raw final iterate. This couples two design choices: the learning-rate schedule that ge

Test-time Reinforcement Learning for Anomalous Video Understanding

arXiv:2609.26099v1 Announce Type: new Abstract: Anomalous video understanding aims to identify abnormal events in videos and interpret their semantic meanings beyond simple anomaly detection. Recent v

safetyarxiv-cs-cv

Testing, not presuming, adequacy: calibrating generative social simulators against emergent network structure

arXiv:2609.24012v2 Announce Type: new Abstract: Validation of generative social simulators often stops at face validity: emergent network structure is compared descriptively, without quantified parame

Text-only adaptation in LLM-based ASR through text denoising

arXiv:2601.20900v4 Announce Type: replace-cross Abstract: Adapting large language model (LLM)-based automatic speech recognition (ASR) systems to new domains using text-only data is a significant yet

safetyarxiv-cs-cl

Text, Pixels, or Both? Evaluating Input Representations for Multimodal Document QA

arXiv:2609.22628v1 Announce Type: new Abstract: Every document QA system begins with a choice that is rarely studied on its own: whether to feed the model page images, extracted text, or both. We isol

researcharxiv-cs-ai

The Cartesian Hand: In-Hand Manipulation with All-Linear Fingers

arXiv:2609.25696v1 Announce Type: new Abstract: Robotic manipulation has increasingly pursued human-like dexterous hands with many articulated degrees of freedom, offering rich manipulation capabiliti

applicationsarxiv-cs-ro

The Challenge of Identifying the Origin of Black-Box Large Language Models

arXiv:2503.04332v2 Announce Type: replace-cross Abstract: The tremendous commercial potential of large language models (LLMs) has heightened concerns over their unauthorized use. To address this, we f

applicationsarxiv-cs-lg

The Delegation Blind Spot: Auditing Product Decisions from Agent Choices

arXiv:2609.26642v1 Announce Type: cross Abstract: Successful agent execution need not identify which future product improvement its user would value. We present a decision-specific audit that maps a d

agentsarxiv-cs-lg

The Dynamics of Quasiregular Neural Learning

arXiv:2609.26018v1 Announce Type: new Abstract: Many learning problems combine a dominant regularity with systematic exceptions. Motivated by U-shaped learning in language acquisition, we study this i

The Endless Exam: Mathematical Constructions from Today's Models toward Superintelligence

arXiv:2609.24555v1 Announce Type: new Abstract: We introduce the Endless Exam, a benchmark for measuring mathematical progress from today's models toward artificial superintelligence through fourteen

The Informational Content in Lepto-Variance and Its Relation to Higher Moments

arXiv:2609.25144v1 Announce Type: cross Abstract: Lepto-regression is defined as the machine learning process of constructing a Regression Tree of a target feature on itself. It is a novel, model-free

The Law of Stop: Interruptibility, Injunctions, and the Governance of Agentic AI

arXiv:2609.22882v1 Announce Type: cross Abstract: On June 12, 2026, the U.S. government ordered Anthropic to bar foreign nationals from two of its most capable models within ninety minutes. Unable to

The Moral Check: Strategic AI Governance for the Pacing Problem

arXiv:2609.22869v1 Announce Type: cross Abstract: Technology cannot steer itself. Strategy provides that steering, establishing the rule that purpose and judgment must precede compute capital. As the

The Price of Safety: Benign-Case Utility and Token Overhead of Memory-Poisoning Defenses in LLM Agents

arXiv:2609.22818v1 Announce Type: cross Abstract: Memory-poisoning defenses for LLM agents are typically evaluated by their ability to prevent attacks. However, the traffic they process is rarely adve

The Probabilistic Structure of Large Language Models

arXiv:2609.25134v1 Announce Type: new Abstract: This paper presents a probabilistic perspective on large language models (LLMs), developed with the aim of bringing together, in a single self-contained

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Management

arXiv:2604.02279v2 Announce Type: replace Abstract: Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44

The Sirens' Song: When Proximal Background Context Overshadows Distant Evidence

model-releasesarxiv-cs-lg

arXiv:2609.26718v1 Announce Type: new Abstract: Long-context LLMs focus on retrieving distant evidence from extensive context, yet existing work has largely focused on overcoming distance alone. In th

The Temporal Moderation Gap: Text-to-Video Safety Filters Are Blind to Harm in Motion

model-releasesarxiv-cs-cv

arXiv:2609.26233v1 Announce Type: new Abstract: Text-to-video (T2V) services inherit their safety stack from image generation, pairing a keyword prompt filter with a per-frame checker that blocks a cl

The Wisdom of Artificial Deliberative Crowds

arXiv:2609.22497v1 Announce Type: new Abstract: The aggregation of many lay estimates often outperforms individual expert judgment, a phenomenon known as the wisdom of crowds. While this is usually at

agentsarxiv-cs-ai

Theory for groupoid equivariant neural networks: an approach for steerable CNNs on bounded domains

arXiv:2609.25987v1 Announce Type: new Abstract: Equivariant convolutional neural networks are usually built from a group acting globally on the space of signals. This hypothesis is inappropriate for m

safetyarxiv-cs-lg

Tutorials

Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions

arXiv:2409.02244v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used as ad hoc therapists. While prior research has found that LLMs outperform human couns

tutorialsarxiv-cs-cl

TicTacBench: Benchmarking Timing Closure Capabilities of Coding Agents

arXiv:2609.23363v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led to the emergence of coding agents capable of performing complex engineering tasks, including re

Local Ai

TimeInteract: Towards Real-Time Interactive Intelligence for Streaming Time Series

arXiv:2609.26389v1 Announce Type: new Abstract: Real-world time series evolve continuously, with meaningful changes potentially emerging at any moment. However, existing time-series language models (T

local-aiarxiv-cs-lg

TimeLitmus: A Diagnostic Benchmark for Cross-Modal Understanding and Explanation Faithfulness in Event-Conditioned Time-Series Prediction

arXiv:2609.24677v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to make predictions from numerical time-series histories and textual events. Yet accuracy alone canno

TM-APR: Thermal Temporal-Memory Localization via Analytic Online Adaptation

arXiv:2609.26766v1 Announce Type: new Abstract: Thermal Visual Place Recognition (Thermal VPR) maps camera observations to metric poses within a mapped environment, serving as a prerequisite for auton

agentsarxiv-cs-ro

Toolcompass: Guiding Tool Trialing, Not Suppressing It

arXiv:2609.25678v1 Announce Type: cross Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is tool trialing, i.e

ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents

arXiv:2605.12481v2 Announce Type: replace Abstract: Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operat

agentsarxiv-cs-ai

Hardware

TopoCompress: Topology Aware Token Compression Algorithm for Distributed Edge MoE Inference

arXiv:2609.26061v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models improve capacity with moderate overhead by sparsely activating experts per token. However, deploying MoE across resour

hardwarearxiv-cs-cl

Topological Signal Processing With Unoriented Operators

arXiv:2609.25310v1 Announce Type: new Abstract: Topological signal processing (TSP) processes signals on simplicial complexes with oriented boundary operators, which is the natural choice for flow sig

applicationsarxiv-cs-lg

Topology-Aware Parameter-Efficient Adaptation for Cross-Dataset Retinal Vessel Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.26189v1 Announce Type: new Abstract: Retinal vessel segmentation in multi-domain deployment requires a source model to adapt to domains that differ in imaging conditions and annotation conv

Total Cost of Agency: Exact Attribution of Memory Injection Cost in Multi-Agent LLM Workflows

arXiv:2609.23790v1 Announce Type: new Abstract: Every node in a multi-agent large language model (LLM) workflow retrieves context from memory and injects it into its prompt, where those injected token

ToW3D: Consistency-aware Interactive Point-based Mesh Editing on GANs

arXiv:2609.26078v1 Announce Type: new Abstract: In this paper, we propose ToW3D that enables precise and consistent control over 3D generative adversarial networks (GANs) with the Tug-of-War competiti

researcharxiv-cs-cv

Toward an automated science of the mind

arXiv:2603.20988v2 Announce Type: replace Abstract: Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind. We chart this field

researcharxiv-cs-ai