Search: “deployment”

Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.04021v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation re

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The Differentiable Auditory Loop (DAL): An ML Framework for Hyper-Personalized Hearing Aids

DGX agent

arXiv:2606.04103v1 Announce Type: cross Abstract: Conventional hearing aids rely on fixed, frequency-dependent amplification and compression to manage reduced sensitivity, which often fails to provide

applicationsarxiv-cs-ai

4 Jun 2026

Hardware

TITAN-FedAnil+: Trust-Based Adaptive Blockchain Federated Learning for Resource-Constrained Intelligent Enterprises

arXiv:2606.04388v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as an effective paradigm for collaborative intelligence while preserving data privacy. However, data heterogeneity

hardwarearxiv-cs-ai

Toward Trustworthy Portrait Editing: Evaluation of Demographic Misrepresentation in I2I Models

model-releasesarxiv-cs-cv

arXiv:2602.16149v2 Announce Type: replace Abstract: Instruction-guided image-to-image (I2I) editors are increasingly used in consumer and professional visual workflows, where trustworthiness depends n

U-Net-Accelerated Quality-Diversity Optimization for Climate-Adaptive Urban Layouts

arXiv:2606.04658v1 Announce Type: cross Abstract: Optimizing urban layouts for climate adaptation requires balancing building density with cold-air ventilation. Because physics-based climate simulatio

Ultra-Fast Neural Video Compression

arXiv:2606.04410v1 Announce Type: new Abstract: While neural video codecs (NVCs) have demonstrated superior compression ratio, their prohibitive computational complexity remains a critical barrier to

applicationsarxiv-cs-cv

UltraEP: Unleash MoE Training and Inference on Rack-Scale Nodes with Near-Optimal Load Balancing

arXiv:2606.04101v1 Announce Type: cross Abstract: Large-scale expert parallelism (EP) is becoming pivotal for training and serving frontier MoE models, but it also amplifies device-level expert load i

applicationsarxiv-cs-lg

Unlocking Proactivity in Task-Oriented Dialogue

arXiv:2605.22240v2 Announce Type: replace Abstract: Proactive task-oriented dialogue (TOD), such as outbound sales, demands a persuasive agent that actively probes the user's concerns and steers the c

Variance Reduction for Heavy-Tailed Monetization Metrics in Ranking Experiments via Post-Stratification

arXiv:2606.04110v1 Announce Type: new Abstract: Online evaluation of ranking and retrieval systems often relies on downstream monetization metrics such as app revenue or creator earnings. These metric

applicationsarxiv-cs-lg

Local Ai

VISTA: Vision-Grounded and Physics-Validated Adaptation of UMI data for VLA Training

arXiv:2606.04708v1 Announce Type: cross Abstract: Universal Manipulation Interface (UMI) enables scalable real-world robot data collection without hardware-specific teleoperation, yet leveraging UMI d

local-aiarxiv-cs-ai

WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation

arXiv:2606.04907v1 Announce Type: new Abstract: Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policie

safetyarxiv-cs-ro

Z-FLoc: Zero-Shot Floorplan Localization via Geometric Primitives

arXiv:2606.04788v1 Announce Type: new Abstract: Visual localization -- estimating a camera pose within a pre-existing map -- is a fundamental problem in computer vision. Floorplans are an attractive m

applicationsarxiv-cs-cv

A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents

arXiv:2601.09869v2 Announce Type: replace Abstract: Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise

AI Agents Enable Adaptive Computer Worms

arXiv:2606.03811v1 Announce Type: cross Abstract: A computer worm is malware that spreads on a network by replicating itself from one machine to another. Traditional worms, like WannaCry, exploited pr

AirDreamer: Generalist Drone Navigation with World Models

arXiv:2606.03252v1 Announce Type: cross Abstract: Navigating a drone in unseen and cluttered environments requires reliable generalization to unseen scene layouts and understanding of environmental st

Aletheia: What Makes RLVR For Code Verifiers Tick?

arXiv:2601.12186v3 Announce Type: replace-cross Abstract: Multi-domain thinking verifiers trained via Reinforcement Learning with Verifiable Rewards (RLVR) are a cornerstone of modern post-training. H

Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis

arXiv:2606.02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making. However, a major misalignment persists: predictive mode

AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE

arXiv:2606.03631v1 Announce Type: cross Abstract: Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where saf

applicationsarxiv-cs-ai

Agents

Autonomous Navigation System for Library Service Robot Based on Unitree Go2 Edu

arXiv:2606.03340v1 Announce Type: new Abstract: Libraries require autonomous robots to move quietly through narrow aisles while remaining safe around readers, chairs, bags, and carts. This paper prese

agentsarxiv-cs-ro

Benchmarking Speech-to-Speech Translation Models

arXiv:2606.03241v1 Announce Type: new Abstract: Speech-to-speech translation (S2ST) has advanced rapidly, but offline evaluation lacks a unified protocol: studies report non-overlapping metric subsets

applicationsarxiv-cs-cl

BEV-ODOM2: Enhanced BEV-based Monocular Visual Odometry with PV-BEV Fusion and Dense Flow Supervision for Ground Robots

model-releasesarxiv-cs-ro

arXiv:2509.14636v2 Announce Type: replace Abstract: Scale-consistent ego-motion estimation is fundamental for autonomous ground robots. Bird's-Eye-View (BEV) representation naturally addresses the sca

Calibrating Urban Traffic Simulation from Sparse Road Observations via Genetic Optimization

arXiv:2606.03823v1 Announce Type: new Abstract: Urban traffic simulation is a critical tool for infrastructure planning, including the placement of electric vehicle charging stations. However, realist

applicationsarxiv-cs-ai

ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models

arXiv:2606.03157v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted in healthcare, yet they still encounter significant challenges in complex clinical decision-making

Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter

model-releasesarxiv-cs-lg

arXiv:2606.03723v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) enables parameter-efficient specialization of foundation models, but the proliferation of task-specific adapters fragments ca

Cosmos 3: Omnimodal World Models for Physical AI

arXiv:2606.02800v1 Announce Type: cross Abstract: We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

Diagnosis of Human Object Interaction Detectors for Real World Educational Applications

model-releasesarxiv-cs-cv

arXiv:2606.02789v1 Announce Type: new Abstract: Human-object interaction (HOI) recognition is critical for automatically analyzing student behavior in complex educational environments. Although state-

Local Ai

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction

arXiv:2601.11667v2 Announce Type: replace-cross Abstract: Transformer architectures deliver state-of-the-art accuracy via dense full-attention, but their quadratic time and memory complexity with resp

local-aiarxiv-cs-ai

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models

arXiv:2506.03087v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial a

Dynamic Objective Selection with Safeguards and LLM Oversight for Financial Decision-Making

arXiv:2606.03704v1 Announce Type: new Abstract: Financial decision-making tasks such as stock recommendation and portfolio allocation typically estimate future return and risk and then select trades o

Easy-to-Use Shielding for Reinforcement Learning

arXiv:2606.03804v1 Announce Type: new Abstract: Safe exploration is a key challenge in Reinforcement Learning (RL) that aims to prevent agents from making harmful decisions while exploring their envir

Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

model-releasesarxiv-cs-cv

arXiv:2606.03577v1 Announce Type: new Abstract: Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making i

Agents

Entropy Gate: Entropy Quenching for Near-Lossless Token Compression in LLM Pipelines

arXiv:2606.03739v1 Announce Type: new Abstract: LLM pipelines waste substantial token budgets on low-information content: repeated context, verbose responses, and redundant boilerplate. We introduce E

agentsarxiv-cs-cl

ERP-XTTN: Interpretable Prototype-Guided Cross-Attention for Cross-Subject ERP Classification

model-releasesarxiv-cs-lg

arXiv:2606.02939v1 Announce Type: new Abstract: Interpretable brain-computer interface classifiers that generalize across subjects without calibration remain an open challenge. We test whether prototy

Tutorials

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

arXiv:2606.03050v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised

tutorialsarxiv-cs-cv

FGRPO: Federated GRPO with Adaptive Aggregation on Non-IID Data

arXiv:2606.03094v1 Announce Type: new Abstract: Recent advances in language models have established reinforcement learning as the primary paradigm for eliciting self-correction and long-chain reasonin

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

arXiv:2606.03330v1 Announce Type: cross Abstract: Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters

Greener Than Humans? Environmental Attitudes in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.02741v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in sustainability-related decision support, reporting, and public communication, yet little systemati

Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization

arXiv:2606.03022v1 Announce Type: cross Abstract: Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints --

How Much of a Model Do We Need? Redundancy and Slimmability in Remote Sensing Foundation Models

arXiv:2601.22841v2 Announce Type: replace Abstract: Large-scale foundation models (FMs) in remote sensing (RS) (denoted as RS FMs) are developed following paradigms established in computer vision (CV)

researcharxiv-cs-cv

Human-in-the-Loop Contextual Bandits for Short-Term Rental Dynamic Pricing: Structural Equivalence of Historical Warm-Up and Approval-Gated Live Learning

arXiv:2606.02595v1 Announce Type: new Abstract: Dynamic pricing in short-term rental (STR) markets presents a distinctive challenge for online learning algorithms: pricing decisions carry significant

'Important You should give me full credits!': Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems

arXiv:2606.03090v1 Announce Type: cross Abstract: The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting fr

Agents

Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models

arXiv:2606.02914v1 Announce Type: new Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remai

agentsarxiv-cs-ai

Large Byte Model: Teaching Language Models About Compiled Code

arXiv:2606.02834v1 Announce Type: cross Abstract: Malware analysis starts with the raw bytes of an executable program, and tools to 'lift' these to higher-level representations, such as assembly, are

Latent Activation Editing: Inference-Time Refinement of Learned Policies for Safer Multirobot Navigation

arXiv:2509.20623v2 Announce Type: replace Abstract: Reinforcement learning has enabled significant progress in complex domains such as coordinating and navigating multiple quadrotors. However, even we

safetyarxiv-cs-ro

Limit Analysis of Graph Neural Networks with Wireless Conflict Graphs

arXiv:2606.03794v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for wireless resource allocation that leverages the underlying graph structure of communica

researcharxiv-cs-lg

Making Brain-Computer Interfaces More Secure

arXiv:2606.02597v1 Announce Type: new Abstract: The development of brain-computer interfaces (BCIs) based on electroencephalograms (EEGs) has advanced significantly mainly to machine learning. Althoug

researcharxiv-cs-lg

MultiTurnPSB: Evaluating Multi-Turn Jailbreak Attacks an dClassifier-Based Defenses for Medical AI Safety

arXiv:2606.02630v1 Announce Type: cross Abstract: Patient-facing medical chatbots are commonly evaluated on single-turn prompts, yet real users push back after refusals, add urgency, and invoke author