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arXiv:2609.30272v1 Announce Type: cross Abstract: We present extbf{ENAS}, a hardware-aware Neural Architecture Search (NAS) framework that combines a static feasibility check, a cell-based search spac

hardwarearxiv-cs-ai

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Research

Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks

DGX agent

arXiv:2609.30581v1 Announce Type: cross Abstract: Encrypted training relies on keeping server-side updates low-degree. This constraint traditionally excludes models whose weights inhabit a compact Lie

researcharxiv-cs-lg

28 Sept 2026

Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer Hardware

arXiv:2608.00008v2 Announce Type: replace Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, t

Energy-efficient operation of neural operators for virtual sensing

arXiv:2609.30580v1 Announce Type: new Abstract: Virtual sensing repeatedly reconstructs physical fields from changing observations, often on a fixed geometry. We investigate how shared spatial computa

Enhancing Assessment of Self-Consistency in LLM Explanations using Perturbation Strength

arXiv:2609.30849v1 Announce Type: new Abstract: Prior work has examined the self-consistency of LLM-generated explanations using surface-level perturbation methods. However, the strength of these pert

researcharxiv-cs-cl

Enhancing Photogrammetric Digital Surface Models with Pretrained Diffusion Models and Multimodal Conditioning

arXiv:2609.31199v1 Announce Type: cross Abstract: Large-scale Digital Surface Models (DSMs) can be produced cost-effectively from satellite images via stereo-photogrammetry. However, the resulting 3D

Entropy Regularization: A Free Correction to Cross-Entropy for Verified Demonstrations

arXiv:2609.30572v1 Announce Type: new Abstract: Large language models are often post-trained on expert demonstrations using cross-entropy (CE), even when the downstream objective is not to imitate the

safetyarxiv-cs-lg

EPOC: Endpoint-Preserving Online Correction With Compressed Residual State for Multi-Horizon Time Series Forecasting

arXiv:2609.30929v1 Announce Type: new Abstract: Completed multi-horizon forecasts provide residual feedback for a fixed forecaster, but retaining full residual blocks increases auxiliary state. We pro

Epstein Files Engine: Agentic Search for Investigative Journalism

arXiv:2609.30611v1 Announce Type: cross Abstract: On Jan. 30, 2026, the U.S. Department of Justice released a mixed-media collection concerning Jeffrey Epstein, including about three million pages of

Equation discovery with Bayesian tree-adjoining grammars

model-releasesarxiv-cs-lg

arXiv:2609.31368v1 Announce Type: cross Abstract: Tree-Adjoining Grammars (TAGs) have recently been introduced to Nonlinear System Identification (NLSI) as a means of encoding an entire model class as

Applications

Estimating and Orthogonalizing Unknown Pre-training Gradients for Continual Fine-tuning of Large Language Models

arXiv:2609.30935v1 Announce Type: cross Abstract: Continual fine-tuning is essential for large language models (LLMs) to dynamically adapt to real-world environments, yet it inevitably suffers from ca

applicationsarxiv-cs-ai

Evaluating Cultural Awareness of LLMs for Haitian Creole

arXiv:2609.31506v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit substantial performance disparities between high- and low-resource languages. Beyond lower task performance, they

Agents

Evaluating Real-Time Voice Agents: From Component Quality to Grounded Outcomes

arXiv:2609.30798v1 Announce Type: new Abstract: Real-time voice agents have moved from research prototypes to production deployments, yet the literature describing them is fragmented across three comm

agentsarxiv-cs-ai

Evaluating Sycophancy in Chinese Large Language Models on Factual Questions Derived from Online Search Queries

arXiv:2609.30986v1 Announce Type: new Abstract: As large language models increasingly mediate information access, factually accurate and independent answers are critical. However, these models can exh

Evaluating the accuracy of KV cache reuse techniques

arXiv:2609.31415v1 Announce Type: new Abstract: Position-independent KV cache reuse aims to reduce latency in retrieval-augmented generation by reusing chunk-level KV caches across prompts. We show th

Evaluating the Impact of Adaptive Extended Reality on Human-Robot Interaction Across the Reality-Virtuality Continuum

arXiv:2609.31138v1 Announce Type: new Abstract: As populations in developed countries age and labor shortages intensify, Cybernetic Avatars (CAs) are proposed to extend human capabilities through robo

researcharxiv-cs-ro

Evaluation Is All You Need for Multi-Modal Autonomous Driving

arXiv:2609.30818v1 Announce Type: cross Abstract: Multi-modal planning is promising for autonomous driving by representing multiple plausible behaviors in ambiguous and long-tail scenarios. Existing m

Evaluation is All You Need: Strategic Overclaiming of LLM Reasoning Capabilities Through Evaluation Design

arXiv:2506.04734v3 Announce Type: replace Abstract: Reasoning models represented by the Deepseek-R1-Distill series have been widely adopted by the open-source community due to their strong performance

Hardware

every agent will need a sandbox and the harness should live outside it - separate the brains from the hands great to see nvidia open sourcin…

hardwareharrison-chase--x

every agent will need a sandbox and the harness should live outside it - separate the brains from the hands great to see nvidia open sourcing tools here, agree with Andrew this is part of the harness

Everyday personal AI assistant startup Instinct raises 1B at 10B valuation

model-releasessiliconangle

Instinct, the developer of an artificial intelligence assistant for everyday users, today announced it has raised a colossal 1 billion in a new funding, bringing the company’s valuation to 10 billion.

Evidence-Grounded Auditing of Identification Assumptions in Climate-Policy Causal Evaluations

arXiv:2609.30867v1 Announce Type: new Abstract: Difference-in-differences (DID) studies are widely used to evaluate climate policy, but assessing the evidence supporting their identification assumptio

EviDETR: Preserving Query-Relevant Temporal Evidence for Moment Retrieval and Highlight Detection

arXiv:2609.30724v1 Announce Type: new Abstract: Joint video moment retrieval and highlight detection requires identifying query-relevant temporal segments while estimating clip-level saliency, yet DET

Evolutionary Safety of Recursive Self-Improving AI: Taxonomy, Risk Discovery, and Evaluation

arXiv:2609.31186v1 Announce Type: new Abstract: Artificial intelligence is advancing rapidly, with increasingly capable systems taking larger roles in reasoning, decision-making, scientific discovery,

Applications

EXAONE Demand 1.0: A Time Series Foundation Model for Demand Forecasting

arXiv:2609.30880v1 Announce Type: new Abstract: Time series foundation models (TSFMs) are pretrained on series from diverse domains, where demand series make up only a small fraction. Demand data has

applicationsarxiv-cs-ai

Tools

Excited to share that I'll be speaking at @aiDotEngineer NYC on Oct 12-14. @covacut (@OpenAI) and I will be giving a joint talk about using …

Excited to share that I'll be speaking at @aiDotEngineer NYC on Oct 12-14. @covacut (@OpenAI) and I will be giving a joint talk about using AI for content creation, and some of the AI workflows behind

toolsswyx--x

ExoLaN: Physics-Consistent Context-Aware Dynamics Learning for Exoskeletons

arXiv:2609.31434v1 Announce Type: new Abstract: Task-agnostic assistive exoskeleton control based on human intention offers greater flexibility than conventional approaches that rely on predefined tas

researcharxiv-cs-ro

Exploiting Spatial Structure for Transductive Few-Shot Classification of Whole-Slide Images

arXiv:2609.31040v1 Announce Type: new Abstract: Automating the analysis of whole-slide images (WSIs), a key step in cancer diagnosis, has high clinical value, as it can reduce pathologist's workload w

Exploring the Benefits of Vision Foundation Models for Unsupervised Domain Adaptation

arXiv:2406.09896v3 Announce Type: replace Abstract: Achieving robust generalization across diverse data domains remains a significant challenge in computer vision. This challenge is important in safet

safetyarxiv-cs-cv

Externalized CPDAG Summaries Improve LLM Causal Deduction

arXiv:2609.31071v1 Announce Type: new Abstract: Corr2Cause asks whether a causal claim holds in every DAG compatible with observed correlations and conditional independencies. We frame this as latent-

Factorized axis convolutional gated recurrent unit with dynamic adaptive pooling for remaining useful life prediction of rolling bearings

arXiv:2609.30972v1 Announce Type: new Abstract: Convolutional neural networks (CNN) are widely used to predict the remaining useful life (RUL) of rolling bearings from time-frequency representations (

researcharxiv-cs-ai

Fake News Theories: Harnessing Disciplinary Insights for Computational Modeling, Detection, and Explanation

model-releasesarxiv-cs-lg

arXiv:2609.30427v1 Announce Type: new Abstract: Disinformation research has produced increasingly accurate automated fake-news detectors, but many systems remain difficult to interpret and are weakly

FARE: Forensic Acceptance Region Estimation for Catching Bait-and-Switch Image Generators

arXiv:2609.30982v1 Announce Type: cross Abstract: Modern AI image generators are increasingly deployed as opaque APIs, where customers can query the deployed service, but cannot inspect model weights

Fast Plans, Faithful Actions: Closing the Planning-Execution Gap in Hierarchical Vision-Language-Action Models

arXiv:2609.30833v1 Announce Type: new Abstract: Hierarchical vision-language-action (VLA) systems consist of a high-level vision-language planner and a low-level action expert that generates continuou

researcharxiv-cs-ro

Faster Rates for Federated Variational Inequalities

researchapple-ml-research

In this paper, we study federated optimization for solving stochastic variational inequalities (VIs), a problem that has attracted growing attention in recent years. Despite substantial progress, a si

FAVoR: Measuring and Mitigating Author-Style Homogenization in Federated Personalized Generation

arXiv:2609.30968v1 Announce Type: new Abstract: Large language models are increasingly used as personalized writing assistants, but adapting a model across many authors can compromise individual writi

FeatMark: Feature-level Watermark Protection against Mimicry Attacks with Diffusion Models

arXiv:2609.30980v1 Announce Type: cross Abstract: Text-to-image diffusion models enable data-efficient 'mimicry' attacks, wherein adversaries fine-tune the model on a handful of public photos to synth

Federated Targeted Maximum Likelihood Estimation

arXiv:2609.30503v1 Announce Type: new Abstract: The evidence behind a scientific or operational decision is often held by hospitals, banks, or registries that cannot pool individual observations. Cros

FedHisto-PAST: Parameter-Efficient Stain-Aware Federated Learning for Cross-Site Lung Histopathology Classification

arXiv:2609.31150v1 Announce Type: cross Abstract: Cross-site lung histopathology classification must account for stain variation, non-IID client data, missing classes, and the cost of adapting large p

Feeding BabyLMs Macaroni: Code-Switching Curricula Cause Cross-Lingual Convergence

arXiv:2609.30535v1 Announce Type: new Abstract: Children in multilingual communities often code-switch, using multiple languages in a single utterance. Can we induce cross-lingual alignment in languag

safetyarxiv-cs-cl

Financial Fragility in Societies of LLM Agents: Coordination Failures and Stabilizing Mechanisms

arXiv:2609.30940v1 Announce Type: new Abstract: Individually protective decisions can produce avoidable collective failures. As large language model (LLM) agents take on greater roles in financial dec

First-Order Stationarity of Reverse Diffusions

arXiv:2609.31612v1 Announce Type: cross Abstract: Recent literature has shown a strong connection between optimization and sampling. We develop the corresponding first-order theory for diffusion model

Fixed Points Without Fixed Diffusion: Implicit Neural Sheaves for Convergent Test-Time Computation

arXiv:2609.30277v1 Announce Type: new Abstract: Implicit Graph Neural Networks (IGNNs) define node representations as fixed points of message-passing operators, enabling effectively infinite-depth pro

FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting

arXiv:2512.14253v4 Announce Type: replace Abstract: In this work, we introduce FLAME, a family of extremely lightweight and capable Time Series Foundation Models, which support versatile forecasting t

safetyarxiv-cs-lg

FlatClip: A Geometry-Aware Surface-Level Baseline for fMRI Representation Learning

arXiv:2609.31204v1 Announce Type: cross Abstract: Recent fMRI foundation models differ substantially in the spatial scale at which they represent brain activity. ROI- and connectivity-based models are

FLIP: Final Layer Inference-Time Probing for Vision-Language Models

arXiv:2609.30993v1 Announce Type: cross Abstract: We present FLIP, a final-layer inference-time probe for testing whether a logit-facing intervention site in an open-weight vision-language model (VLM)

Industry

Florida AG James Uthmeier files for an emergency injunction against OpenAI and ChatGPT, asserting the company cannot adequately self-regulate its tech (Axios)

Axios: Florida AG James Uthmeier files for an emergency injunction against OpenAI and ChatGPT, asserting the company cannot adequately self-regulate its tech — Florida Attorney General James Uthmeier

industrytechmeme

Florida gets it: we need an injunction NOW, otherwise we are playing Russian roulette, hoping that some new software package can save us bef…

Florida gets it: we need an injunction NOW, otherwise we are playing Russian roulette, hoping that some new software package can save us before some massive and possibly deadly AI-induced infrastructu

safetygary-marcus--x

Applications

Florida invokes extinction fears in legal bid to halt OpenAI development

Florida has sought a temporary injunction against OpenAI, arguing that large‑language model development without third‑party approved safety guardrails poses an existential threat and preys on vulnerab

applicationsars-technica