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arXiv:2609.39020v1 Announce Type: cross Abstract: We study how well deep neural networks approximate and learn spectral Barron functions. Recent studies have shown that these function classes can be e

tutorialsarxiv-cs-lg

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MiniRep: Robust Reputation-Based Aggregation for Multi-Agent Debate

DGX agent

arXiv:2609.39297v1 Announce Type: new Abstract: Autonomous agents powered by large language models (LLMs) are rapidly evolving into an open agentic ecosystem. To support trustworthy collaboration, ind

agentsarxiv-cs-ai

1 Oct 2026

Mitigating Memorization In Language Models

arXiv:2410.02159v3 Announce Type: replace-cross Abstract: Language models (LMs) can 'memorize' information, i.e., encode training data in their weights in such a way that inference-time queries can le

local-aiarxiv-cs-ai

Mitigating Object Hallucination in Large Vision-Language Models via False Discovery Controlled Visual Data Splitting

arXiv:2609.38979v1 Announce Type: new Abstract: Multiple object hallucination, where large vision-language models (LVLMs) generate objects not supported by the visual input, is a persistent challenge

researcharxiv-cs-cv

Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision

arXiv:2609.39525v1 Announce Type: cross Abstract: Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intract

local-aiarxiv-cs-lg

Mitigating the Length-Scaling Tax with Online Distillation

arXiv:2609.38854v1 Announce Type: cross Abstract: Length scaling during reinforcement-learning (RL) post-training is often viewed as a sign of improved reasoning ability, especially on difficult probl

safetyarxiv-cs-ai

MM-FinEval: A Multi-Task Multimodal Benchmark for Real-World Financial Forecasting

model-releasesarxiv-cs-ai

arXiv:2609.38523v1 Announce Type: cross Abstract: Financial forecasting from earnings conference calls requires models to reason over complex corporate disclosures, market expectations, and subtle com

MOBA-VL: Event-Localized Multi-Turn Reinforcement Learning for Real-Time MOBA Commentary

arXiv:2609.38428v1 Announce Type: new Abstract: Real-time commentary for Multiplayer Online Battle Arena (MOBA) esports requires a vision-language model (VLM) to narrate a live match second by second,

ModalFidelity: Routing Modalities for Deepfake Detection on a Budget

arXiv:2609.38246v1 Announce Type: cross Abstract: Deepfakes no longer need to fake a whole video. Generators that read the transcript now alter only the few seconds in which a video's meaning turns, s

researcharxiv-cs-ai

Tutorials

ModSec-Learn: Boosting ModSecurity with Machine Learning

arXiv:2406.13547v2 Announce Type: replace Abstract: ModSecurity is widely recognized as the standard open-source Web Application Firewall (WAF), maintained by the OWASP Foundation. It detects maliciou

tutorialsarxiv-cs-lg

MoEless: Efficient MoE LLM Serving with Serverless Experts

arXiv:2603.06350v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) increasingly adopt Mixture-of-Experts (MoE) architectures to scale efficiently under stringent resource constrain

local-aiarxiv-cs-ai

MoFlow: Multi-Objective Agentic Workflow Generation

arXiv:2609.38294v1 Announce Type: new Abstract: We study the generation of agentic workflows that jointly optimize multiple objectives, such as accuracy, cost, latency, robustness, and consistency. Ex

agentsarxiv-cs-ai

Molecular Property Prediction under Structural Shift with Tabular Foundation Models

arXiv:2609.38744v1 Announce Type: new Abstract: Predicting molecular properties for compounds that differ structurally from labeled training molecules is important for drug discovery and materials des

More Choices, Fewer Decisions: Ordinal-Scale Bias in JEV-like Direct-Decision Models

arXiv:2609.38827v1 Announce Type: new Abstract: Direct-decision models turn text into low-latency structured labels and scores, making them attractive for classification and automatic evaluation. Yet

safetyarxiv-cs-ai

MotionWeave: Learning Motion-Centered Future Dynamics for Vision-Language-Action Policies

arXiv:2609.39324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently incorporated world models to provide richer dynamic supervision beyond sparse action labels. However

local-aiarxiv-cs-cv

MRI Super-Resolution with RCDM/WaveMix and Task-Aware Segmentation

arXiv:2609.39083v1 Announce Type: new Abstract: Super-resolution and quality enhancement of 1.5,T brain MRI are normally validated with image-fidelity metrics, although their purpose is to improve dow

Multi-agent discussion gains less when dissent is withheld

model-releasesarxiv-cs-cl

arXiv:2609.38324v1 Announce Type: cross Abstract: Multi-agent systems of LLMs add discussion to majority voting and are therefore expected to be more capable. However, empirical reports conflict on wh

Multi-Link Safety Filtering for VLA Policies Around Moving Hazards

arXiv:2609.40007v1 Announce Type: cross Abstract: A vision-language-action (VLA) policy can finish a manipulation task while knocking over objects unrelated to it, so task success alone does not show

safetyarxiv-cs-cv

Multi-LLM Collaborative Alignment via Stackelberg Games

arXiv:2609.39076v1 Announce Type: new Abstract: A pool of language models can collaborate and improve collectively by learning from one another's responses. These interactions depend on the instructio

safetyarxiv-cs-ai

Multidimensional Observer Model and Perceptual Dimensions of Human Image Quality Assessment

arXiv:2609.38487v1 Announce Type: new Abstract: Judging image quality is not only ecologically relevant to everyday human tasks, but also underpins many machine vision tasks such as image generation.

researcharxiv-cs-cv

Multimodal Flow: Unified Flow Modeling of Language and Vision in Embedding Spaces

arXiv:2609.40362v1 Announce Type: new Abstract: We present Multimodal Flow, a fully continuous generative model of language and vision. Most unified multimodal models either model both language and qu

Mutual Equilibrium: Multimodal Representation Learning through Reciprocal Feedback

arXiv:2609.39456v1 Announce Type: cross Abstract: This work proposes a mutual feedback architecture, MEQ, that refines the two inputs, of possibly different modalities, into a pair of coupled embeddin

researcharxiv-cs-cv

MVP-SLAM: Multi-Camera Visual-Inertial Floorplan-Prior SLAM

arXiv:2609.39596v1 Announce Type: new Abstract: Indoor building construction sites are demanding environments for visual SLAM, where variable lighting and repetitive, low-textured structures make the

safetyarxiv-cs-ro

NAQD Env: A benchmark for selective withdrawal in language agents

model-releasesarxiv-cs-ai

arXiv:2609.38460v1 Announce Type: new Abstract: Language agents must revise planned actions when evidence changes, permission is revoked, or a stop instruction arrives. A useful response is selective:

NarrativeSteward: Coordinating Delegation, Guidance, and Verification in Agent-Assisted Interactive Narrative Authoring

arXiv:2609.39333v1 Announce Type: cross Abstract: Autonomous AI agents can turn authors' goals into interactive narratives by independently organizing and carrying out generation and revision. As agen

agentsarxiv-cs-ai

NavHarness: Adaptive Goals for Agentic Vision-Language Navigation

arXiv:2609.39915v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents

local-aiarxiv-cs-cv

Near-Linear Accuracy Bounds for Moreau--Yosida Unadjusted Langevin Sampling

arXiv:2609.40193v1 Announce Type: new Abstract: We establish near-linear accuracy bounds for the classical Moreau--Yosida unadjusted Langevin algorithm (MYULA). The target is pipropto e^{-f-g}, where

Hardware

NetApp and Nvidia rethink storage for AI factories

Storage architecture is being rewritten for artificial intelligence factories. Traditional enterprise storage was designed around workloads that scaled in relatively predictable ways. AI changes that

hardwaresiliconangle

Industry

NetApp’s ‘sleeping giant’ moment as AI brings new data buyers

Artificial intelligence has pulled data infrastructure out of the back office and into conversations with buyers who never had to think about storage before. For longtime storage providers, that shift

industrysiliconangle

Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning

arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor

NeurDuo-EEG: A Long-Sequence EEG Foundation Model with Persistent State and Explicit Memory

arXiv:2609.38587v1 Announce Type: new Abstract: Electroencephalography (EEG) is recorded continuously over hours, with relevant dynamics spanning timescales from milliseconds to hours. Most EEG founda

researcharxiv-cs-lg

Neuro-Symbolic Predicate Learning for Semantic Safe Robot Control

model-releasesarxiv-cs-ro

arXiv:2609.39594v1 Announce Type: new Abstract: As robots are increasingly deployed in everyday environments, ensuring their safety has become a central challenge. Existing methods often encode safety

Applications

NEXUS: Perceptive Whole-Body Control for Terrain-Adaptive Teleoperation

arXiv:2609.39000v1 Announce Type: new Abstract: Whole-body teleoperation requires a humanoid robot to reproduce a human operator's behavior even when their terrains differ. This demands that the robot

applicationsarxiv-cs-ro

NinaXander: Feasibility and Limits of Composing Frozen Language Models Across Architecture Families via a Shared Latent Space

arXiv:2609.38261v1 Announce Type: cross Abstract: In this paper we propose NinaXander, a series of composed language models obtained by connecting layers of frozen language models from different archi

researcharxiv-cs-ai

NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance

model-releasesarxiv-cs-ai

arXiv:2507.09601v3 Announce Type: replace-cross Abstract: Financial text embeddings must distinguish changes in event status, perspective, and obligations even when passages share similar wording. NMI

No Corners Cut: State-Grounded Transitions for Mid-Stream Prompt Switches in Video Generation

arXiv:2609.38691v1 Announce Type: new Abstract: Streaming video generators allow users to dynamically modulate video synthesis via mid-stream prompt switching. Existing streaming methods can respond t

No Task Vector Is an Island: A Comprehensive Study on the Composability of Task Vectors from On-Policy Distillation

arXiv:2609.39405v1 Announce Type: new Abstract: Task vectors provide a simple mechanism for composing learned capabilities through model merging. However, the composability of task vectors produced by

no way will this government properly police companies that it has a 10% equity stake in

no way will this government properly police companies that it has a 10% equity stake in 🚨 BREAKING: Trump REJECTS nationalizing OpenAI and Anthropic but says the US government might take an Intel-styl

safetygary-marcus--x

NodeGround: A Node Classification Benchmark in the Graph Foundation Model Era

arXiv:2609.39673v1 Announce Type: new Abstract: Can a pretrained graph model replace training and tuning a separate predictor for each dataset? Answering this requires evaluating prediction quality al

Non-Invasive Inspection of Water Canals Using Dronar

arXiv:2609.40178v1 Announce Type: new Abstract: Open concrete canals play a vital role in water transportation, serving as primary water infrastructure for millions of people across the Phoenix, Arizo

researcharxiv-cs-ro

Not all solutions are created equal: An analytical dissociation of functional and representational similarity in deep linear neural networks

arXiv:2609.38998v1 Announce Type: new Abstract: A foundational principle of connectionism is that perception, action, and cognition emerge from parallel computations among simple, interconnected units

Hardware

Nvidia ties AI factory economics to tokens and power efficiency

Artificial intelligence factory economics increasingly depend on more than access to high-performance graphics processing units. As agentic systems draw on multiple models, databases and tools, the en

hardwaresiliconangle

Applications

Observability Analysis and Online Calibration of Visual-Inertial-Wheel Odometry for 4WIS4WID Mobile Robots

arXiv:2609.38462v1 Announce Type: new Abstract: In this paper, we present a visual-inertial-wheel odometry (VIWO) framework with online calibration for four-wheel independently steered and driven (4WI

applicationsarxiv-cs-ro

OccluDex: Hierarchical 3D Visuo-Tactile Representation Learning for Egocentric Dexterous Manipulation under Self-Occlusion

arXiv:2609.39017v1 Announce Type: new Abstract: Reliable dexterous manipulation requires continuous estimation of object geometry and hand-object contact throughout interaction. With egocentric sensin

researcharxiv-cs-ro

Occlusion-Aware, Quasi-Static, Stability-Oriented Trajectory Planning on Uneven Terrain

arXiv:2609.39105v1 Announce Type: new Abstract: Autonomous navigation in unstructured off-road environments requires reasoning about both vehicle--terrain interaction and environmental unknowns. We pr

agentsarxiv-cs-ro

OctoNest: Adaptive Cross-Device Execution through Stateful Control

arXiv:2606.20487v2 Announce Type: replace Abstract: Computer use agents are expanding from single-device operation toward cross-device systems that coordinate tasks across heterogeneous environments.

researcharxiv-cs-cl

Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models

model-releasesarxiv-cs-cl

arXiv:2609.39346v1 Announce Type: new Abstract: Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (SL

OGPO: One-Step Generative Policy Optimization for Real-Time Robot Control

arXiv:2601.20701v2 Announce Type: replace Abstract: Real-time robot control demands fast action generation. Diffusion and flow matching policies for robot control require multi-step sampling, limiting

safetyarxiv-cs-ro