Search: “framework”

rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

arXiv:2609.19104v1 Announce Type: cross Abstract: Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured sta

safetyarxiv-cs-ai

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Social Laws for Multi-agent Coordination in Stochastic Environments

DGX agent

arXiv:2609.18929v1 Announce Type: cross Abstract: In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous re

safetyarxiv-cs-ai

17 Sept 2026

Sparse Bayesian Modeling of EEG Channel Interactions Improves P300 Brain-Computer Interface Performance

arXiv:2602.17772v3 Announce Type: replace-cross Abstract: Electroencephalography (EEG)-based P300 brain-computer interfaces (BCIs) enable communication without physical movement by detecting stimulus-

researcharxiv-cs-lg

STUNet-Fusion: Spatiotemporal Needle-Tip Localization in Ultrasound Video via Multi-Channel Motion Fusion

arXiv:2609.18546v1 Announce Type: new Abstract: Needle-tip localization in ultrasound remains challenging because the needle may appear weak, discontinuous, or partially invisible, while imaging artif

researcharxiv-cs-cv

Tabular Deep Learning vs Classical Machine Learning for Urban Land Cover Classification

arXiv:2609.19010v1 Announce Type: cross Abstract: Urban Land Cover (ULC) classification plays a crucial role in urban planning, environmental monitoring, and sustainable development. We study this tas

The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

arXiv:2408.07702v2 Announce Type: cross Abstract: Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's q

Hardware

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a

hardwarearxiv-cs-ai

The Other Half of the Memory Wall: Serving 35B MoEs from SSD with Trained Routing Prediction

arXiv:2609.18063v1 Announce Type: new Abstract: Mixture-of-experts (MoE) inference on consumer hardware is bounded by weight memory: a 35B-class model is 19.5GB at 4-bit, and sparsity shrinks the comp

Think Before You Comfort: Reflective Cognitive Alignment for Protocol-Grounded Elderly Stimulation Agents

arXiv:2609.17536v1 Announce Type: new Abstract: Cognitive Stimulation Therapy (CST) offers non-pharmacological support for elders with cognitive impairment, yet scalability remains constrained by reli

safetyarxiv-cs-cl

Tutorials

Time-Aligned Evolving Concept Graphs for Scientific Relation Forecasting

arXiv:2609.18163v1 Announce Type: new Abstract: Forecasting scientific relations can guide discovery by identifying promising connections before they emerge. Existing approaches often model concept se

tutorialsarxiv-cs-ai

Towards Interaction Regulation from Human Feedback via Free Energy Minimization

arXiv:2609.18853v1 Announce Type: cross Abstract: A central challenge across control and learning is the design of mechanisms regulating the interactions between humans and autonomous agents. Inspired

TRACER: Adaptive Multi-Robot Social Navigation via Joint Human-Response Prediction and Interaction-Aware Replanning

model-releasesarxiv-cs-ro

arXiv:2609.18776v1 Announce Type: new Abstract: Multi-robot navigation in human-shared spaces is inherently interactive: coordinated robot motions influence how nearby entities respond, while those re

Agents

UAVs Meet Embodied Intelligence: Bridging Human Intents and Flying Dynamics Via Harnessing Physical-Digital AI Agents

arXiv:2609.18326v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) extend embodied intelligence into continuous three-dimensional space, where perception, reasoning, physical embodiment,

agentsarxiv-cs-ro

Uncertainty-Aware Continual Learning for Open-World Intent Discovery Under an evolving Label Space

arXiv:2609.17866v1 Announce Type: cross Abstract: Real-world intelligent systems increasingly operate under open-world conditions, where user intents are not fixed or exhaustively known a priori and m

applicationsarxiv-cs-cl

Vision-Language Grounded Task-Context-Aware Imitation Learning for Robotic Disassembly

arXiv:2609.17714v1 Announce Type: new Abstract: Real-world robotic disassembly requires long-horizon execution, where robots must perform ordered sequences of manipulation tasks across multiple parts

Tutorials

When Audit Quality Fails to Predict Downstream Utility: A Counterfactual Study of Synthetic-Data Selectors for Low-Resource African NLP

arXiv:2609.18960v1 Announce Type: new Abstract: Quality-aware synthetic-data selection rests on a proxy: examples that an LLM judge rates as good should also help a downstream model learn. In a contro

tutorialsarxiv-cs-cl

When to Call an LLM: A Confidence-Gated Hybrid for Cost-Effective Emotion Recognition in Conversational AI

arXiv:2609.17977v1 Announce Type: new Abstract: Emotion recognition in conversation (ERC) is a production capability behind agent-assist prompts, escalation routing, and post-call analytics in contact

safetyarxiv-cs-ai

XingChen-AGI/Xing4.0-29B-A4B MoE

model-releasesr-localllama

I find another new model at HF: https://huggingface.co/XingChen-AGI/Xing4.0-29B-A4B 'Xing4.0-29B-A4B is a next-generation large language model in the Xing series (formerly TeleChat), developed by Chin

Adaptive Bayesian Partner Selection for Federated Clinical Centers

arXiv:2609.16446v1 Announce Type: new Abstract: Federated learning (FL) in healthcare faces pronounced heterogeneity and temporal concept drift across clinical centers, where evolving patient populati

applicationsarxiv-cs-lg

Affect-Prototype Guided Fusion for Open-Vocabulary Incomplete Multi-modal Emotion Recognition

arXiv:2609.16962v1 Announce Type: new Abstract: Open-vocabulary multimodal emotion recognition (OV-MER) aims to generate open natural-language emotion labels from multimodal affective cues. In real-wo

applicationsarxiv-cs-ai

Artificial Intelligence-Enabled Space Robot Operations: Technologies, Challenges and Prospects

arXiv:2609.16880v1 Announce Type: new Abstract: Space robots are increasingly expected to perform long-duration, contact-rich, and multi-stage operations with limited human intervention. Recent advanc

Agents

AURA: Agentic Diagnosis and Refinement for Production Recommender Systems at Scale

arXiv:2609.16625v1 Announce Type: cross Abstract: How and why does a recommender system fail the users it serves? Oftentimes, practitioners are left to improve their algorithms based on a combination

agentsarxiv-cs-ai

Benchmarking Factual Robustness of LLMs via Multi-conversation Persuasion

arXiv:2609.16777v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as primary knowledge retrieval interfaces, their robustness against extit{persuasion attacks}---attem

safetyarxiv-cs-cl

Bridging Learned Visual Perception and Symbolic Belief-Space Planning

arXiv:2609.16884v1 Announce Type: new Abstract: In partially observable settings, agents must act without full knowledge of the world state and rely on uncertain state-estimation pipelines. Obtaining

Cloud CISO Perspectives: How Google monitors AI threats and advances AI defenses

model-releasesgoogle-cloud-ai

Welcome to the first Cloud CISO Perspectives for September 2026. Today, Sandra Joyce shares the latest details on Google’s visibility into how attackers are using AI, and how we’re using AI to stop th

Comment on arXiv:2607.01233: Survivorship Bias in Published-Paper Baselines for Research-Idea Distributions

arXiv:2609.15996v1 Announce Type: new Abstract: Chen, Zhao, and Cohan introduce a valuable distributional evaluation of LLM-generated research ideas. This comment raises a narrower identification conc

safetyarxiv-cs-cl

Do You Have Freestyle? Expressive Humanoid Locomotion via Audio Control

arXiv:2512.23650v3 Announce Type: replace Abstract: Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse

Local Ai

Dual Randomized Smoothing: Beyond Global Noise Variance

arXiv:2512.01782v4 Announce Type: replace-cross Abstract: Randomized Smoothing (RS) is a prominent technique for certifying the robustness of neural networks against adversarial perturbations. With RS

local-aiarxiv-cs-ai

Early-Bird Decoding: Accelerating Diffusion LLMs with Learnable Block Sizes and Parallel Sampling

arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative

EBL: Efficient Broad Learning for Distributed Adaptive Harmonic Analysis

arXiv:2609.16358v1 Announce Type: cross Abstract: Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominate

researcharxiv-cs-lg

Efficient One-to-Many Translation with Joint Multi-Stream Diffusion

arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both

Efficient Quantization-Aware Distillation with Cross-Modal Alignment for Edge Vision-Language Models

arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained

safetyarxiv-cs-cv

Efficient Reasoning Distillation: Small Video-Language Models via Synthetic CoT and Difficulty-Aware Fine-Tuning

arXiv:2609.16255v1 Announce Type: cross Abstract: We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our

EgoPathBench: Evaluating Zero-Shot Egocentric Waypoint Decision-Making in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.16610v1 Announce Type: new Abstract: Zero-shot waypoint navigation requires vision-language models to select, from the current first-person observation, a sequence of spatial actions that i

Enhancing Low-resolution Image Representation Through Normalizing Flows

arXiv:2601.06834v2 Announce Type: replace Abstract: Low-resolution image representation can be regarded as a special form of sparse representation that retains only low-frequency information while dis

researcharxiv-cs-cv

Event-based Selective Attention for Multi-resolution Fast Region of Interest (ROI) Detection

arXiv:2609.17134v1 Announce Type: new Abstract: Neuromorphic vision systems operate under strict constraints on bandwidth, memory, and energy, particularly at the edge, motivating early mechanisms for

applicationsarxiv-cs-cv

Tutorials

EventEgoHands++: Event-based Egocentric 3D Hand Mesh Reconstruction with Real Dataset

arXiv:2609.17189v1 Announce Type: new Abstract: 3D hand mesh reconstruction is a challenging yet essential task for downstream applications, including human-robot interaction and AR/VR. Although conve

tutorialsarxiv-cs-cv

Fairness at Every Intersection: Uncovering and Mitigating Intersectional Biases in Multimodal Clinical Predictions

arXiv:2412.00606v2 Announce Type: replace Abstract: Biases in automated clinical decision-making using Electronic Healthcare Records (EHR) impose significant disparities in patient care and treatment

Local Ai

Fast-Convergent Meta-RL via Gradient-Clustered BS Sampling for Edge Caching

arXiv:2609.16370v1 Announce Type: cross Abstract: Wireless edge caching networks typically consist of many independent Base Stations (BSs), each facing its own request rate and content popularity prof

local-aiarxiv-cs-lg

From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling

arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since

Agents

Generating Individual Travel Diaries Using Large Language Models Informed by Census and Land-Use Data

arXiv:2509.09710v3 Announce Type: replace-cross Abstract: This study introduces a Large Language Model (LLM) scheme for generating key attributes of travel diaries in agent-based transportation models

agentsarxiv-cs-ai

Goal-oriented probabilistic forecasting for dynamic PRB allocation in 5G networks

arXiv:2609.17297v1 Announce Type: cross Abstract: Efficient physical resource block (PRB) allocation in 5G networks requires accurate demand forecasting. Conventional methods minimize symmetric error

researcharxiv-cs-lg

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning

arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori

How Orange uses agents to make FinOps everyone's responsibility

model-releasesgoogle-cloud-ai

At Orange, the leading France-based multinational telecom provider, there are days when engineering teams set aside their delivery backlogs and spend the day cleaning up cloud spend together. There's

Intelligent Interaction Techniques (IIxT) - Proposal

arXiv:2609.16295v1 Announce Type: cross Abstract: Interaction techniques (IxTs) are the low-level, reusable components out of which user interfaces are designed, including menus, scroll bars, text inp

Interactive Memory Learning for Long-Term Conversations

arXiv:2609.17088v1 Announce Type: new Abstract: Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these s

safetyarxiv-cs-ai

Interpreting and Steering LLM Agents for Social Simulations

arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the s

Latent Undertow: How Ordinary Typos Break Probes

model-releasesarxiv-cs-cl

arXiv:2609.15994v1 Announce Type: new Abstract: LLMs handle ordinary typing variation fluently: a typo or missing punctuation leaves both user intent and the model's response substantively unchanged.