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Dynamic UGV-UAV Cooperative Path Planning in Uncertain Environments

arXiv:2604.25267v1 Announce Type: new Abstract: This paper addresses the Dynamic UGV-UAV Cooperative Path Planning (DUCPP) problem involving one unmanned ground vehicle (UGV) assisted by one or more u

researcharxiv-cs-ro

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Human DGX agent

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Edge-Cloud Collaborative Reconstruction via Structure-Aware Latent Diffusion for Downstream Remote Sensing Perception

DGX agent

arXiv:2604.25319v1 Announce Type: new Abstract: The exponential surge in high-resolution remote sensing data faces a severe bottleneck in satellite-to-ground transmission. Limited downlink bandwidth f

researcharxiv-cs-cv

29 Apr 2026

Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance

arXiv:2604.25554v1 Announce Type: cross Abstract: Collision-free motion is often aided by tactile and proximity sensors distributed on the body of the robot due to their resistance to occlusion as opp

Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR

arXiv:2604.24770v1 Announce Type: new Abstract: Despite recent progress in automatic speech recognition (ASR), elderly ASR (EASR) remains challenging due to limited training data and the distinct acou

Elite-Driven Support Vector Machines for Classification

arXiv:2604.25158v1 Announce Type: cross Abstract: Support vector machines (SVMs) are a standard tool for binary classification, but their classical formulations are purely data-driven and offer no dir

Emergent Self-Attention from Astrocyte-Gated Associative Memory Dynamics

arXiv:2604.25481v1 Announce Type: cross Abstract: We introduce a Hopfield-type associative memory in which effective connectivity is multiplicatively modulated by astrocytic gains evolving under an en

Enhancing Financial Report Question-Answering: A Retrieval-Augmented Generation System with Reranking Analysis

arXiv:2603.16877v2 Announce Type: replace Abstract: Financial analysts face significant challenges extracting information from lengthy 10-K reports, which often exceed 100 pages. This paper presents a

Enhancing SignSGD: Small-Batch Convergence Analysis and a Hybrid Switching Strategy

arXiv:2604.25550v1 Announce Type: new Abstract: SignSGD compresses each stochastic gradient coordinate to a single bit, offering substantial memory and communication savings, but its 1-bit quantizatio

EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling

model-releasesarxiv-cs-ro

arXiv:2604.25782v1 Announce Type: cross Abstract: Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While

ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation

arXiv:2604.24876v1 Announce Type: new Abstract: Text guided 3D medical image segmentation offers a flexible alternative to class based and spatial prompt based models by allowing users to specify regi

Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts

arXiv:2410.06723v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) have emerged as powerful pretrained encoders for computational pathology, but their robustness under clinic

Evaluating LLM Safety Under Repeated Inference via Accelerated Prompt Stress Testing

arXiv:2602.11786v2 Announce Type: replace Abstract: Traditional benchmarks for large language models (LLMs), such as HELM and AIR-BENCH, primarily assess safety through breadth-oriented evaluation acr

Evaluation without Generation: Non-Generative Assessment of Harmful Model Specialization with Applications to CSAM

arXiv:2604.25119v1 Announce Type: new Abstract: Auditing the fine-tunes of open-weight generative models for harmful specialization has become a new governance challenge for model hosting platforms. T

Evolving Multi-Channel Confidence-Aware Activation Functions for Missing Data with Channel Propagation

arXiv:2602.13864v2 Announce Type: replace-cross Abstract: Learning in the presence of missing data can result in biased predictions and poor generalizability, among other difficulties, which data impu

EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming

arXiv:2604.25499v1 Announce Type: new Abstract: Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane

arXiv:2604.25885v1 Announce Type: cross Abstract: Graph neural networks such as ParticleNet and transformer based networks on point clouds such as ParticleTransformer achieve state-of-the-art performa

Exploring Reasoning Reward Model for Agents

arXiv:2601.22154v2 Announce Type: replace-cross Abstract: Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However

Exploring Remote Photoplethysmography for Neonatal Pain Detection from Facial Videos

arXiv:2604.25680v1 Announce Type: new Abstract: Unaddressed pain in neonates can lead to adverse effects, including delayed development and slower weight gain, emphasising the need for more objective

Tutorials

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds

arXiv:2604.25289v1 Announce Type: cross Abstract: Practically, training diffusion models typically requires explicit time conditioning to guide the network through the denoising sampling process. Espe

tutorialsarxiv-cs-cv

Faithful Autoformalization via Roundtrip Verification and Repair

arXiv:2604.25031v1 Announce Type: new Abstract: When an LLM formalizes natural language, how do we know the output is faithful? We propose a roundtrip verification approach which does not require grou

Faithfulness-QA: A Counterfactual Entity Substitution Dataset for Training Context-Faithful RAG Models

arXiv:2604.25313v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) models frequently produce answers grounded in parametric memory rather than the retrieved context, undermining the

FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments

arXiv:2604.25135v1 Announce Type: new Abstract: Large Language Models are being increasingly deployed as the decision-making core of autonomous agents capable of effecting change in external environme

FARM: Enhancing Molecular Representations with Functional Group Awareness

arXiv:2410.02082v4 Announce Type: replace Abstract: We introduce Functional Group-Aware Representations for Small Molecules (FARM), a novel foundation model designed to bridge the gap between SMILES,

Fast Geometric Embedding for Node Influence Maximization

arXiv:2506.07435v3 Announce Type: replace-cross Abstract: Computing classical centrality measures such as betweenness and closeness is computationally expensive on large-scale graphs. In this work, we

FCMBench-Video: Benchmarking Document Video Intelligence

arXiv:2604.25186v1 Announce Type: new Abstract: Document understanding is a critical capability in financial credit review, onboarding, and remote verification, where both decision accuracy and eviden

Feasible-First Exploration for Constrained ML Deployment Optimization in Crash-Prone Hierarchical Search Spaces

arXiv:2604.25073v1 Announce Type: new Abstract: Deploying machine learning models under production constraints requires joint optimization over model family, quantization scheme, runtime backend, and

FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices

arXiv:2604.25421v1 Announce Type: new Abstract: Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devices without centralizing private data, yet in mobile

Agents

FGDM: Reasoning Aware Multi-Agentic Framework for Software Bug Detection using Chain of Thought and Tree of Thought Prompting

arXiv:2604.24831v1 Announce Type: cross Abstract: Deep Learning methods are becoming prominent in automated software bug detection; however, they lack the global understanding of the given code. Conse

agentsarxiv-cs-lg

Fractionally Supervised Classification with Maxima Nominated Samples

arXiv:2604.25145v1 Announce Type: cross Abstract: Fractionally supervised classification (FSC) offers a flexible framework for combining labeled and unlabeled data in model-based classification, but e

Safety

Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment

arXiv:2604.25136v1 Announce Type: new Abstract: We propose Frictive Policy Optimization (FPO), a framework for learning language model policies that regulate not only what to say, but when and how to

safetyarxiv-cs-cl

From Ambiguity to Accuracy: The Transformative Effect of Coreference Resolution on Retrieval-Augmented Generation systems

arXiv:2507.07847v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a crucial framework in natural language processing (NLP), improving factual consistency and redu

From Chatbots to Confidants: A Cross-Cultural Study of LLM Adoption for Emotional Support

arXiv:2604.25525v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used not only for instrumental tasks, but as always-available and non-judgmental confidants for emotional

From Cursed to Competitive: Closing the ZO-FO Gap via Input-to-State Stability

arXiv:2604.25372v1 Announce Type: cross Abstract: While it is generally understood that zeroth-order (ZO) algorithms have an extra dependency on their number of iterations for any choice of parameters

From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models

arXiv:2510.18030v2 Announce Type: replace Abstract: Structured pruning is a practical approach to deploying large language models (LLMs) efficiently, as it yields compact, hardware-friendly architectu

Agents

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling

arXiv:2604.25847v1 Announce Type: cross Abstract: Optimization modeling underpins real-world decision-making in logistics, manufacturing, energy, and public services, but reliably solving such problem

agentsarxiv-cs-lg

From Syntax to Emotion: A Mechanistic Analysis of Emotion Inference in LLMs

arXiv:2604.25866v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in emotionally sensitive human-AI applications, yet little is known about how emotion recognition is

Local Ai

From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generation

arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world

local-aiarxiv-cs-cl

Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External Solver

arXiv:2604.25067v1 Announce Type: cross Abstract: Forecasting when AI systems will become capable of meaningfully accelerating AI research is a central challenge for AI safety. Existing benchmarks mea

G-Loss: Graph-Guided Fine-Tuning of Language Models

arXiv:2604.25853v1 Announce Type: new Abstract: Traditional loss functions, including cross-entropy, contrastive, triplet, and su pervised contrastive losses, used for fine-tuning pre-trained language

GAIA-v2-LILT: Multilingual Adaptation of Agent Benchmark beyond Translation

arXiv:2604.24929v1 Announce Type: new Abstract: Agent benchmarks remain largely English-centric, while their multilingual versions are often built with machine translation (MT) and limited post-editin

GCA-BULF: A Bottom-Up Framework for Short-Term Load Forecasting Using Grouped Critical Appliances

arXiv:2604.24766v1 Announce Type: new Abstract: With the rise of time-of-use and tiered electricity pricing, energy consumers are encouraged to adopt peak-shifting strategies by automatically controll

Applications

GEGLU-Transformer for IMU-to-EMG Estimation with Few-Shot Adaptation

arXiv:2604.25670v1 Announce Type: new Abstract: Reliable estimation of neuromuscular activation is a key enabler for adaptive and personalized control in wearable robotics. However, surface electromyo

applicationsarxiv-cs-ro

Generalizable Human Gaussian Splatting via Multi-view Semantic Consistency

arXiv:2604.25466v1 Announce Type: new Abstract: Recently, generalizable human Gaussian splatting from sparse-view inputs has been actively studied for the photorealistic human rendering. Most existing

Safety

Generative AI Carries Non-Democratic Biases and Stereotypes: Representation of Women, Black Individuals, Age Groups, and People with Disability in AI-Generated Images across Occupations

arXiv:2409.13869v2 Announce Type: replace-cross Abstract: In this study, I investigate how generative artificial intelligence (AI) systems reproduce and reinforce societal biases, with a specific focu

safetyarxiv-cs-cl

Tutorials

Generative diffusion models for spatiotemporal influenza forecasting

arXiv:2604.24913v1 Announce Type: new Abstract: Forecasting infectious disease incidence can provide important information to guide public health planning, yet is difficult because epidemic dynamics a

tutorialsarxiv-cs-lg

Genie Sim 3.0 : A High-Fidelity Comprehensive Simulation Platform for Humanoid Robot

model-releasesarxiv-cs-ro

arXiv:2601.02078v2 Announce Type: replace Abstract: The development of robust and generalizable robot learning models is critically contingent upon the availability of large-scale, diverse training da

GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity.

researcharxiv-cs-cv

Golden RPG: Confidence-Adaptive Region-Aware Noise for Compositional Text-to-Image Generation

arXiv:2604.25314v1 Announce Type: new Abstract: Compositional text-to-image (T2I) generation requires a model to honour multiple sub-prompts that describe distinct image regions. Recent work shows tha