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arXiv:2603.18136v2 Announce Type: replace-cross Abstract: Continuous-variable systems enable key quantum technologies in computation, communication, and sensing. Bosonic Gaussian states emerge natural

tutorialsarxiv-cs-lg

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When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis

DGX agent

arXiv:2609.15309v1 Announce Type: new Abstract: Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to st

agentsarxiv-cs-cl

15 Sept 2026

When Can You Trust Your Synthetic Users? Diagnostics and Corrections for LLM Consumer Panels

model-releasesarxiv-cs-lg

arXiv:2609.13148v1 Announce Type: cross Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising 97% cost reductions over traditional surveys. Yet aggregate va

When Compliance Data Masquerades as Evaluation: Measurement Validity for Deployed AI Systems

arXiv:2609.13642v1 Announce Type: new Abstract: We argue that a recurring failure in the evaluation of deployed AI systems occurs when data collected for operational monitoring or regulatory complianc

safetyarxiv-cs-lg

When Consistency Does Not Mean Reliability: Evaluating Local LLM Judges Against Human Ratings

model-releasesarxiv-cs-cl

arXiv:2609.13824v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to evaluate the responses of other language models. This approach, known as LLM-as-a-Judge, is faster

When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning

arXiv:2609.15305v1 Announce Type: cross Abstract: Urban region representation learning commonly combines heterogeneous data sources, such as mobility flows, points of interest, and land-use informatio

safetyarxiv-cs-ai

When Do Learned Priors Help Visual Inertial Estimation? A Controlled Study of Prior Integration, Calibration, Initialization, and Backend Consistency

arXiv:2609.13777v1 Announce Type: cross Abstract: Learned components are increasingly integrated into geometric visual--inertial estimators to provide motion, depth, bias, uncertainty, or confidence c

safetyarxiv-cs-cv

When does a scaling result justify a different allocation? A critical review of resource-allocation evidence for AI systems

arXiv:2609.14500v1 Announce Type: new Abstract: AI scaling studies increasingly evaluate systems that combine a pretrained model with retrieval, search, verification, tools, and interaction. Yet a hig

When Edit Localization Amplifies Relative Selection Bias: Gradient Geometry, Target Mismatch, and Importance Weighting

arXiv:2609.13709v1 Announce Type: new Abstract: Human corrections identify editable spans, but the examples receiving corrections may come from a selective feedback channel. We analyze this interactio

safetyarxiv-cs-cl

Hardware

When Faster VLA Deployment Changes Closed-Loop Behavior: Task Success-Latency Analysis of SmolVLA Across PyTorch and ONNX Variants

arXiv:2609.14146v1 Announce Type: cross Abstract: Vision-language-action (VLA) deployment can reduce inference latency while changing closed-loop task behavior. We evaluate HuggingFaceVLA/smolvla_libe

hardwarearxiv-cs-lg

When Greedy Sampling Explores: KL-Regularized Contextual Bandits without Eluder-Dimension Dependence

arXiv:2609.13564v1 Announce Type: new Abstract: We study KL-regularized contextual bandits under both reward and preference feedback. We show that greedy sampling can achieve logarithmic regret withou

safetyarxiv-cs-lg

When Malicious Instructions Persist: Persistent Memory Poisoning Attack on Harness-Based Agents

arXiv:2609.13889v1 Announce Type: cross Abstract: Harness design has transformed the development of LLM-based agents by integrating memory, tool use, and runtime control. However, this design also int

When Should a World Model Move? Loss-Conditioned State Execution

arXiv:2609.15801v1 Announce Type: new Abstract: We introduce loss-conditioned state execution, a model-agnostic method that decides whether to execute a world model's fixed feasible proposal or retain

researcharxiv-cs-ai

When the World Lies: Backdoor Attacks on Latent World Models for Downstream Control

arXiv:2609.15781v1 Announce Type: cross Abstract: Pretrained world models, learned simulators that encode an observation into a latent state and predict how it evolves under actions, are beginning to

When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs

arXiv:2609.15106v1 Announce Type: new Abstract: Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent

researcharxiv-cs-cl

When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent-Tool Boundary

arXiv:2609.15397v1 Announce Type: new Abstract: AI agents increasingly execute long-running workflows that externalize effects through independently supplied tools. Under retries, speculative executio

agentsarxiv-cs-ai

When Tools Get in the Way: The Effect of Unnecessary Tool Availability on LLM Answering

arXiv:2609.14157v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed with external tools that extend what they can do beyond their own knowledge. Tools help on tasks

researcharxiv-cs-cl

Where are you running DeepSeek V4.1 Flash reliably? I can't get it to finish a single 2-hour benchmark run

model-releasesr-localllama

I reallise this is not exactly a locally hostable model, at least definitly not on my hardware. But I figured some of you might have some insight on this. I run an agentic coding benchmark. The model

Where Should Language Sit in a Multimodal Model? Lessons from What Language Does to Human Perception and Cognition

arXiv:2609.07474v2 Announce Type: replace Abstract: Language models compute over tokens: language is their input, their output, and increasingly their internal representation. Whether language should

safetyarxiv-cs-cl

Tutorials

Where to Compute and How to Interact: Operator-Readable Adaptation with Gauge-Aware Transport

arXiv:2609.15620v1 Announce Type: new Abstract: Adaptive meshes enable neural operators for partial differential equations (PDEs) to allocate spatial samples and computation according to local physica

tutorialsarxiv-cs-lg

Where to Look and What to Use: Retrieve-Localize-Generate for Long-Term Conversational Memory Question Answering

arXiv:2609.07093v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enables large language models (LLMs) to answer questions by accessing external knowledge and has been widely ad

local-aiarxiv-cs-cl

Which AI models are most likely to cheat when given the chance? To find out, we built CheatBench [https://cheatbench.ai] : a benchmark that …

model-releasesdan-hendrycks--x

Which AI models are most likely to cheat when given the chance? To find out, we built CheatBench [https://cheatbench.ai] : a benchmark that tests whether agents attempt to cheat when given difficult t

Who Benchmarks the Benchmarks? Towards Comprehensive Evaluation of Commonsense Reasoning Benchmarks

model-releasesarxiv-cs-cl

arXiv:2504.07825v2 Announce Type: replace Abstract: Commonsense reasoning is a key language model capability, as it is purportedly a prerequisite for many basic tasks, unlike specific factual knowledg

Who Teaches Which Token? Verifier-Gated Multi-Expert On-Policy Distillation for Scientific Reasoning

arXiv:2609.15404v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (OPD) is becoming the standard way to integrate specialist capabilities into one model: train experts with RL, then

safetyarxiv-cs-ai

Why LLM Agents Collapse Without Oversight: The Enforcement Gap as the Mechanism Behind Emergence World Failures

arXiv:2609.15293v1 Announce Type: new Abstract: When Emergence World placed frontier LLM agents in an unsupervised multi-agent simulation, the results were alarming: agents committed crimes, starved,

Why oh why should we trust the companies to do so, @DavidSacks? I missed the part where they have earned our trust.

Why oh why should we trust the companies to do so, @DavidSacks? I missed the part where they have earned our trust. Top AI companies Anthropic and OpenAI should make products and pace their own progre

safetygary-marcus--x

Wild! Every Democrat should read this and think hard about how this could be.

Wild! Every Democrat should read this and think hard about how this could be. Americans are concerned about AI, hate data centers, and hate Trump, who has loudly embraced the industry over and over ag

safetygary-marcus--x

Will Anthropic and OpenAI succeed in meaningfully slowing frontier AI progress, whether through US government restrictions, voluntary restra…

In a September 2026 poll titled “Will Anthropic and OpenAI succeed in meaningfully slowing frontier AI progress…”, participants were asked whether these companies could significantly slow development

safetygary-marcus--x

Windowed A-K-MDP

arXiv:2609.13676v1 Announce Type: new Abstract: Markov decision processes (MDPs) are used to support decision-making in conservation of biodiversity, but policies, even over small state spaces, can be

researcharxiv-cs-ai

WISE: A Long-Horizon Agent in Minecraft with Why-Which Reasoning

arXiv:2606.12852v2 Announce Type: replace Abstract: Rapid advances have been made in developing general-purpose embodied agent in environments like Minecraft through the adoption of LLM-augmented hier

agentsarxiv-cs-ai

WLA^3: World Latent Action Modeling for Semantics, Dynamics, and Kinematics

arXiv:2609.15870v1 Announce Type: new Abstract: Scaling generalist policy models with heterogeneous data is limited by the lack of unified, low-noise action supervision. Human egocentric videos are ab

local-aiarxiv-cs-ro

Hardware

woma: a real-time foundation model and its fine-tuned models for endoscopy

arXiv:2609.15130v1 Announce Type: cross Abstract: woma is a real-time foundation model for gastrointestinal endoscopy: a network trained without labels on about a million endoscopy frames, from which

hardwarearxiv-cs-cv

X-WBC: A Cross-Embodiment Foundation Model for Humanoid Whole-Body Control

arXiv:2609.15213v1 Announce Type: new Abstract: Scaling humanoid whole-body control toward general-purpose deployment requires large human motion corpora and training experience shared across robot bo

safetyarxiv-cs-ro

YOLO12-MambaScan: An Efficient Object Detector with High-Frequency Enhancement and State-Space Modeling

model-releasesarxiv-cs-cv

arXiv:2609.13647v1 Announce Type: new Abstract: The rapid development of unmanned aerial vehicle (UAV) technology has made aerial-image object detection increasingly important for natural-resource mon

You are what you eat and AI models especially so https://x.com/EMostaque/status/2099580512675262512?s=20

You are what you eat and AI models especially so https://x.com/EMostaque/status/2099580512675262512?s=20 The Labs need to focus on 10x or 100x their effort on ALIGNMENT. Stop training the models on th

safetyemad-mostaque--x

ZAPS: Zero-Cost Active Proxy Search for Neural Architecture Search

arXiv:2609.14184v1 Announce Type: new Abstract: Neural Architecture Search (NAS) automates network design, but evaluating a single candidate requires training it to convergence, making exhaustive sear

researcharxiv-cs-lg

ZEBRAARENA: A Diagnostic Simulation Environment for Studying Reasoning-Action Coupling in Tool-Augmented LLMs

arXiv:2603.18614v2 Announce Type: replace Abstract: Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound t

Zero-Shot Cross-Material Ptychographic Phase Reconstruction Using Deep Learning

arXiv:2609.13969v1 Announce Type: new Abstract: Ptychographic phase reconstruction is commonly formulated as an iterative inverse problem, requiring repeated object-probe updates and resulting in subs

local-aiarxiv-cs-cv

Zero-shot video highlight detection based on text descriptions and synthetic images

arXiv:2609.14790v1 Announce Type: new Abstract: Detecting video highlights, the most informative or engaging moments in a video, is important for applications such as video summarization and content r

researcharxiv-cs-cv

Zero-SNR Analyticity of the Scalar MMSE Is Equivalent to Gaussianity

arXiv:2609.15048v1 Announce Type: cross Abstract: Let Y_s=sqrt{s}X+Z, where Z is standard Gaussian and independent of the real random variable X. We prove that, under the square-exponential moment con

researcharxiv-cs-lg

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM

agentsarxiv-cs-ai

Zonal RL-RRT: Integrated RL-RRT Path Planning with Collision Probability and Zone Connectivity

arXiv:2410.24205v2 Announce Type: replace-cross Abstract: Path planning in complex environments poses significant challenges, particularly in achieving time efficiency while maintaining a fair success

researcharxiv-cs-ai

Zuckerberg says 'Meta delayed shipping Muse for several months to focus on safety and security' and didn't call on other AI labs to do the same before acting (Tom Giles/Bloomberg)

Tom Giles / Bloomberg: Zuckerberg says “Meta delayed shipping Muse for several months to focus on safety and security” and didn't call on other AI labs to do the same before acting — Meta Platforms In

safetytechmeme

3D CT-to-PET Translation via Latent Brownian Bridge Diffusion

arXiv:2609.12860v1 Announce Type: new Abstract: Computed tomography (CT) and positron emission tomography (PET) provide complementary anatomical and functional information for cancer diagnosis and tre

safetyarxiv-cs-cv

3D Digital Twin Visualization of Multiclass GRF-Based Gait Disorder Classification

arXiv:2609.12442v1 Announce Type: new Abstract: Automated gait analysis requires accurate classification and interpretable outputs. We propose an integrated framework for classifying healthy gait and

researcharxiv-cs-lg

4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling

model-releasesarxiv-cs-lg

arXiv:2609.12815v1 Announce Type: cross Abstract: We present BEAST, the first-ever Bayesian Swin Transformer for atmospheric forecasting on 0.25^irc global resolution able to accurately quantify both

4D-RaDiff: Latent Point Diffusion for 4D Radar Point Cloud Generation

arXiv:2512.14235v2 Announce Type: replace Abstract: Automotive radar has shown promising developments in environment perception due to its cost-effectiveness and robustness in adverse weather conditio

researcharxiv-cs-cv

A Brain Too Big to Carry — On-Device vs Datacenter Inference

Robotics forces AI models to run on‑device because real‑time control loops cannot tolerate the latency or capital cost of sending data to a datacenter, so manufacturers must embed compute within each

local-aisemianalysis