Search: “deployment”

Failure Is the Mother of Success: Recovering Supervision with Grounding Hindsight

arXiv:2610.21018v1 Announce Type: new Abstract: When every rollout for a problem fails, GRPO receives neither a successful exemplar nor a nonzero group-relative advantage, so it learns nothing from ex

safetyarxiv-cs-ai

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

FALCON: FPGA-Accelerated Latency-Certifiable Occupancy Networks for Camera-Based Autonomous Driving

DGX agent

arXiv:2610.22143v1 Announce Type: new Abstract: A perception system that must brake for a pedestrian does not need a low average latency. It must deliver an answer before the deadline on every frame,

model-releasesarxiv-cs-cv

16 Oct 2026

Local Ai

Fault Detection and Bit-Error Rate Diagnostics in Optical Wireless Links Using Edge-AI

arXiv:2610.21402v1 Announce Type: new Abstract: Optical Wireless Communication (OWC) systems provide high-bandwidth, spatially secure, and RF-interference-free digital transmission. However, direct fr

local-aiarxiv-cs-lg

FDE-Gym: The Last Mile of AI Delivery

arXiv:2610.22350v1 Announce Type: new Abstract: Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world custom

Local Ai

FedSkillGit: Federated Skill Evolution via Version Control

arXiv:2610.21348v1 Announce Type: new Abstract: Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience. In real-world deploym

local-aiarxiv-cs-ai

FedSumUp: User-Auditable Privacy-Aware Representation Sharing for Resource-Constrained Federated Intelligence

arXiv:2610.21194v1 Announce Type: cross Abstract: Existing federated data condensation methods face privacy risks, as uploaded synthetic data may preserve sensitive information and remain vulnerable t

Applications

FilterFusion: Prior-Guided Adaptive Filter Fusion for Efficient Video Denoising

arXiv:2610.21505v1 Announce Type: new Abstract: Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inco

applicationsarxiv-cs-cv

Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Memory Writing

arXiv:2610.22196v1 Announce Type: new Abstract: External-memory systems extend language-model applications beyond a context window, but their quality depends critically on the model executing the writ

Improving Environment-Agnostic Coding Agents: The Role of Scaffolding

arXiv:2610.22289v1 Announce Type: new Abstract: Stronger language models may increasingly construct useful procedures for themselves, reducing the advantage of developer-supplied scaffolding. We inves

KODA: Kinematics--Observation Data Alignment for Humanoid Learning from Human Egocentric Demonstration

arXiv:2610.21152v1 Announce Type: new Abstract: Training humanoid whole-body vision-language-action (VLA) policies requires costly robot demonstrations with aligned robot-view observations and control

Large Language Models Naively Recover Ethnicity from Individual Records

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

Learning When to Think: Utility-Guided Adaptive Reasoning for Efficient Text Retrieval

arXiv:2610.21030v1 Announce Type: cross Abstract: Reasoning-conditioned embeddings can improve retrieval by progressively refining semantic constraints. However, additional reasoning may introduce ove

LLMR: Knowledge Distillation with a Large Language Model-Induced Reward

arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) ta

Market Incentives for AI Safety Investment

arXiv:2610.21607v1 Announce Type: new Abstract: Despite their practical significance, modern AI systems pose significant societal risks, including toxicity, malicious use, and misinformation. Their mi

MARS: A Momentum-Aware Adaptive Rating System for Personalized Assessment

arXiv:2610.21685v1 Announce Type: cross Abstract: Adaptive assessment systems personalize learning by estimating learner proficiency and recommending suitable questions. However, many existing approac

MetaExp: Learning to Self-Improve through Experience via Verifiable Cross-Task Environment Scaling

arXiv:2610.21492v1 Announce Type: new Abstract: Language-model agents can accumulate interaction feedback, but reliably turning that feedback into reusable experience remains challenging. Existing met

Applications

Money-Mule Detection as a Relational Learning Problem: A Study on the RBIH NFPC Dataset

arXiv:2610.21314v1 Announce Type: new Abstract: Money-mule networks move criminal funds through many small transfers, each of which looks ordinary on its own. What marks an account as a mule lies outs

applicationsarxiv-cs-ai

Local Ai

MOSS: Mode-Oriented Source Shaping for Robot Flow Matching Policies

arXiv:2610.22193v1 Announce Type: new Abstract: In robotic manipulation, the same observation often admits multiple feasible actions. Generative policies such as diffusion and flow matching naturally

local-aiarxiv-cs-ro

Plans Are Not Executions: Adapting Frozen World-Model Planners to Controller-Induced Execution Shift

arXiv:2610.22041v1 Announce Type: new Abstract: World-model planners evaluate candidate trajectories by predicting their future consequences, implicitly relying on the plan-to-motion relationship lear

researcharxiv-cs-ro

PRISM: PRIvileged Sibling-guided Multi-Agent Topology Design

arXiv:2610.20628v1 Announce Type: new Abstract: Multi-agent systems (MAS) based on large language models (LLMs) have become a powerful way to address complex problems, and their effectiveness depends

agentsarxiv-cs-cl

QuasiLeak-Bench: Evaluating LLM-Based Privacy Detectors on Policy-Conditioned Quasi-Evidence Group Recovery

arXiv:2610.21333v1 Announce Type: new Abstract: Natural language messages often contain quasi-identifiers that are weak in isolation but can jointly reveal an individual's private attributes. We call

RAC: A Relational Agent Contract for Constraint-Governed Engineering Tasks

arXiv:2610.20935v1 Announce Type: new Abstract: Engineering agents must produce artifacts that satisfy exact, coupled constraints. Existing solutions often require agents to make semantic decisions an

Race to Recovery: Designing Advanced Safety Systems for Autonomous Driving via Learning Autonomous Racing

arXiv:2610.20873v1 Announce Type: new Abstract: Vehicles that lose control at the handling limit through icing, hydroplaning, or an abrupt evasive maneuver fall outside the operating envelope of produ

Ranked Right, Sized Wrong: Ensemble Spread Fails Silently at Streamflow Extremes

arXiv:2610.20947v1 Announce Type: cross Abstract: Deep learning models, particularly Long Short-Term Memory networks, are increasingly used for operational streamflow forecasting, with ensemble spread

Reinforcement Learning-driven Diffusion Models: Language, Vision, and Beyond

arXiv:2610.21539v1 Announce Type: new Abstract: Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following

REKI: Registering Knowledge in VLAs

arXiv:2610.22178v1 Announce Type: cross Abstract: We introduce REKI, a 2.4B vision-language-action model (VLA) pretrained exclusively on public data that sets a new Pareto frontier between performance

safetyarxiv-cs-cv

Retrieved but Not Read: Understanding Why Search-Augmented LLMs Fail to Use Available Evidence

arXiv:2610.21731v1 Announce Type: cross Abstract: Web search allows LLMs to access up-to-date information, but it remains unclear why they sometimes produce outdated answers even when relevant evidenc

SCCL-DT: Semantic-Conflict-Aware Contrastive Learning with Dual-Rule Teacher Distillation for Zero-Shot Chest X-Ray Diagnosis

arXiv:2610.22094v1 Announce Type: new Abstract: Contrastive vision-language pre-training supports zero-shot chest X-ray diagnosis, but standard objectives treat every off-diagonal image-report pair in

researcharxiv-cs-cv

Selection-Safe Conformal Early Exit: Distribution-Free Coverage under Adaptive Depth

arXiv:2610.20773v1 Announce Type: new Abstract: Calibrating a conformal prediction set at each early exit does not preserve coverage once a data-dependent exit is selected. We construct one terminal p

Sparse Federated Echo State Networks for Time-Series Classification via Smooth-L1 Regularization

arXiv:2610.21742v1 Announce Type: new Abstract: Echo State Networks (ESNs), as lightweight implementations of reservoir computing, provide efficient solutions for temporal data processing in resource-

researcharxiv-cs-lg

StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction

arXiv:2610.21081v1 Announce Type: new Abstract: Score-based diffusion methods usually perturb data with Brownian Gaussian noise, corresponding to a light-tailed forward stochastic differential equatio

researcharxiv-cs-lg

Applications

TGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping

arXiv:2610.20901v1 Announce Type: cross Abstract: Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation. Given the task of using a knife to 'slice bread,'

applicationsarxiv-cs-ai

The Self-Improvement Problem

arXiv:2610.21646v1 Announce Type: new Abstract: With the rise of large language models, agentic systems are becoming increasingly autonomous, as they write code, call tools, revise prompts, and propos

Towards Emotion Consistency Analysis of Large Language Models in Emotional Conversational Contexts

arXiv:2605.06476v2 Announce Type: replace Abstract: In this work, we conduct an analysis to examine the consistency of Large Language Models (LLMs) with respect to their own generated responses in an

Trajectory-Level Speculation with Semantic Verification for Tool-Using Agents

arXiv:2610.21463v1 Announce Type: cross Abstract: Large language model agents solve tasks through long sequences of tool calls, and the prevailing design has a single strong model generate every step,

TS-WAM: Temporal Latent Actions and World-Action Coupling for Vision-Language Robot Control

arXiv:2610.21922v1 Announce Type: new Abstract: Many vision-language-action policies rely on action-labeled robot demonstrations and lack an explicit mechanism for predicting future visual states. The

Unfragmenting Nawatl NMT: Single-Variant Specialization for Masewalkopa

arXiv:2610.22110v1 Announce Type: new Abstract: In minoritized (low-resource) language technologies, a common response to data sparsity is to aggregate text across multiple varieties and treat the com

researcharxiv-cs-cl

Uni-PNP: Unified Prehensile and Non-prehensile Policy Learning for Generalizable Object Pose Reaching

arXiv:2610.21735v1 Announce Type: new Abstract: Object manipulation often requires combining non-prehensile actions with grasping. However, existing approaches typically develop these capabilities sep

Unified Perceptive Fall Safety for Humanoids

arXiv:2602.16511v3 Announce Type: replace Abstract: Reliable fall recovery is critical for humanoids operating in cluttered environments. Unlike quadrupeds or wheeled robots, humanoids undergo high-en

Value as Memory: Online Value-Guided Post-training for General Robot Policies

arXiv:2610.22368v1 Announce Type: new Abstract: Real-world post-training of generalist robot policies faces two challenges: partial observability makes action selection ambiguous, while offline post-t

Watts If? A Benchmark for Counterfactual Reasoning About the AI Data Center Buildout

arXiv:2610.21397v1 Announce Type: new Abstract: An AI data center is committed years before it draws a watt: a few discrete choices (grid or on-site gas, evaporative or dry cooling, which county to fi

When Should a Low-Light Pipeline Generate? Auditable Risk Control for Selective Generative Enhancement

arXiv:2610.21335v1 Announce Type: new Abstract: Generative low-light enhancers recover plausible texture but may hallucinate structure; restoration networks preserve structure but can leave regions un

researcharxiv-cs-cv

Hardware

When the KV Cache Is Slower Than the GPU: Scaling Remote KV Tiers for Context-Parallel Prefill

arXiv:2610.21500v1 Announce Type: cross Abstract: Reusing the attention KV cache across requests is a standard way to cut prefill cost in long-context LLM serving, and production systems increasingly

hardwarearxiv-cs-lg

When to Ask for Help: A Decision-Theoretic Account and Measurement Standard for Slow-Module Scheduling in Dual-System Vision-Language-Action Models

arXiv:2610.21160v1 Announce Type: new Abstract: Dual-system vision-language-action (VLA) models pair a high-frequency fast policy with a slow, expensive module, and published trigger mechanisms for in

Why Do Agent Teams Fail Across Boundaries? A Failure Taxonomy for Agent-to-Agent Systems with Private States

arXiv:2610.19342v2 Announce Type: replace-cross Abstract: Agents are increasingly interacting with other agents that act for different principals (people or organizations on whose behalf they work), s

A Reference Architecture for Integrating Agentic AI into Enterprise Software: Responsibilities, Interactions, and Variability

arXiv:2610.14818v1 Announce Type: new Abstract: Agentic AI moves generative AI applications toward systems that coordinate reasoning, enterprise context, model inference, and external actions. Integra

15 Oct 2026

Agency as a New Organizing Abstraction for Computer Science

arXiv:2610.17410v1 Announce Type: new Abstract: Advances in large-scale machine learning have enabled agentic AI systems: persistent, autonomous computational entities that pursue goals, initiate acti

safetyarxiv-cs-ai

15 Oct 2026

AI Representations of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups Using GPT-Based LLMs

arXiv:2610.16042v1 Announce Type: cross Abstract: The increasing use of artificial intelligence (AI) in mental health applications raises concerns about its potential to internalize and perpetuate soc