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Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning

arXiv:2505.16176v2 Announce Type: replace Abstract: In mathematical reasoning, data selection strategies predominantly rely on static, externally defined metrics, which fail to adapt to the evolving c

safetyarxiv-cs-ai

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Model Releases

Dynamic Tool Dependency Retrieval for Lightweight Function Calling

DGX agent

arXiv:2512.17052v4 Announce Type: replace Abstract: Function calling agents powered by Large Language Models (LLMs) select external tools to automate complex tasks. On-device agents typically use a re

model-releasesarxiv-cs-lg

20 Apr 2026

DyTact: Capturing Dynamic Contacts in Hand-Object Manipulation

arXiv:2506.03103v2 Announce Type: replace Abstract: Reconstructing dynamic hand-object contacts is essential for realistic manipulation in AI character animation, XR, and robotics, yet it remains chal

safetyarxiv-cs-cv

Early Detection of Acute Myeloid Leukemia (AML) Using YOLOv12 Deep Learning Model

arXiv:2604.16082v1 Announce Type: cross Abstract: Acute Myeloid Leukemia (AML) is one of the most life-threatening type of blood cancers, and its accurate classification is considered and remains a ch

ECG-Lens: Benchmarking ML & DL Models on PTB-XL Dataset

arXiv:2604.15822v1 Announce Type: cross Abstract: Automated classification of electrocardiogram (ECG) signals is a useful tool for diagnosing and monitoring cardiovascular diseases. This study compare

EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence

arXiv:2509.14977v2 Announce Type: replace Abstract: Ultrasound imaging has become the preferred imaging modality for early cancer screening due to its advantages of non-ionizing radiation, low cost, a

researcharxiv-cs-cv

Eco-Bee: A Personalised Multi-Modal Agent for Advancing Student Climate Awareness and Sustainable Behaviour in Campus Ecosystems

arXiv:2604.15327v1 Announce Type: cross Abstract: Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environme

Applications

Efficient Video Diffusion Models: Advancements and Challenges

arXiv:2604.15911v1 Announce Type: new Abstract: Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains co

applicationsarxiv-cs-cv

Elucidating the SNR-t Bias of Diffusion Probabilistic Models

arXiv:2604.16044v1 Announce Type: new Abstract: Diffusion Probabilistic Models have demonstrated remarkable performance across a wide range of generative tasks. However, we have observed that these mo

safetyarxiv-cs-cv

Enabling Predictive Maintenance in District Heating Substations: A Labelled Dataset and Fault Detection Evaluation Framework based on Service Data

arXiv:2511.14791v2 Announce Type: replace-cross Abstract: Early detection of faults in district heating substations is imperative to reduce return temperatures and enhance efficiency. However, progres

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction

arXiv:2604.16238v1 Announce Type: new Abstract: Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such for

safetyarxiv-cs-lg

Enhancing Hazy Wildlife Imagery: AnimalHaze3k and IncepDehazeGan

arXiv:2604.16284v1 Announce Type: new Abstract: Atmospheric haze significantly degrades wildlife imagery, impeding computer vision applications critical for conservation, such as animal detection, tra

researcharxiv-cs-cv

Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning

arXiv:2503.13543v2 Announce Type: replace-cross Abstract: Federated Prototype Learning (FedPL) has emerged as an effective strategy for handling data heterogeneity in Federated Learning (FL). In FedPL

local-aiarxiv-cs-ai

Environment-Adaptive Solid-State LiDAR-Inertial Odometry

arXiv:2604.15864v1 Announce Type: new Abstract: Solid-state LiDAR-inertial SLAM has attracted significant attention due to its advantages in speed and robustness. However, achieving accurate mapping i

researcharxiv-cs-ro

EnvScaler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis

arXiv:2601.05808v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are expected to be trained to act as agents in various real-world environments, but this process relies on rich a

Tutorials

Estimating Joint Interventional Distributions from Marginal Interventional Data

arXiv:2409.01794v2 Announce Type: replace-cross Abstract: In this paper we show how to exploit interventional data to acquire the joint conditional distribution of all the variables using the Maximum

tutorialsarxiv-cs-lg

Evaluating LLM Simulators as Differentially Private Data Generators

arXiv:2604.15461v1 Announce Type: cross Abstract: LLM-based simulators offer a promising path for generating complex synthetic data where traditional differentially private (DP) methods struggle with

agentsarxiv-cs-cl

Evaluating LLMs as Human Surrogates in Controlled Experiments

arXiv:2604.15329v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to simulate human responses in behavioral research, yet it remains unclear when LLM-generated data

Evaluating quality in synthetic data generation for large tabular health datasets

arXiv:2604.15961v1 Announce Type: new Abstract: There is no consensus in the field of synthetic data on concise metrics for quality evaluations or benchmarks on large health datasets, such as historic

researcharxiv-cs-lg

Applications

Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design

arXiv:2604.16279v1 Announce Type: new Abstract: Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse s

applicationsarxiv-cs-lg

EventCrab: Harnessing Frame and Point Synergy for Event-based Action Recognition and Beyond

arXiv:2411.18328v2 Announce Type: replace Abstract: Event-based Action Recognition (EAR) possesses the advantages of high-temporal resolution capturing and privacy preservation compared with tradition

researcharxiv-cs-cv

EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs

arXiv:2604.15787v1 Announce Type: cross Abstract: We introduce EVIL (extbf{EV}olving extbf{I}nterpretable algorithms with extbf{L}LMs), an approach that uses LLM-guided evolutionary search to discover

EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems

arXiv:2510.13220v2 Announce Type: replace Abstract: A fundamental limitation of current AI agents is their inability to learn complex skills on the fly at test time, often behaving like 'clever but cl

Examining the Relationship between Scientific Publishing Activity and Hype-Driven Financial Bubbles: A Comparison of the Dot-Com and AI Eras

arXiv:2509.11982v2 Announce Type: replace Abstract: Financial bubbles often arrive without much warning, but create long-lasting economic effects. For example, during the dot-com bubble, innovative te

researcharxiv-cs-lg

Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data

arXiv:2604.15380v1 Announce Type: cross Abstract: We present an exascale workflow for materials discovery using atomistic graph foundation models built on HydraGNN. We jointly train on 16 open first-p

'Excuse me, may I say something...' CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations

arXiv:2604.15588v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into scientific workflows presents exciting opportunities to accelerate biomedical discovery. However,

ExoNet: Multimodal Deep Learning for TESS Exoplanet Candidate Identification via Phase-Folded Light Curves, Stellar Parameters, and Multi-Head Attention Fusion

arXiv:2604.15560v1 Announce Type: cross Abstract: NASA's Transiting Exoplanet Survey Satellite (TESS) has identified thousands of exoplanet candidates, yet many remain unconfirmed due to the limitatio

local-aiarxiv-cs-lg

Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents

arXiv:2604.15877v1 Announce Type: new Abstract: As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory

Explainable Iterative Data Visualisation Refinement via an LLM Agent

arXiv:2604.15319v1 Announce Type: cross Abstract: Exploratory analysis of high-dimensional data relies on embedding the data into a low-dimensional space (typically 2D or 3D), based on which visualiza

Exploitation Over Exploration: Unmasking the Bias in Linear Bandit Recommender Offline Evaluation

arXiv:2507.18756v2 Announce Type: replace Abstract: Multi-Armed Bandit (MAB) algorithms are widely used in recommender systems that require continuous, incremental learning. A core aspect of MABs is t

safetyarxiv-cs-lg

Exploring LLM-based Verilog Code Generation with Data-Efficient Fine-Tuning and Testbench Automation

arXiv:2604.15388v1 Announce Type: cross Abstract: Recent advances in large language models have improved code generation, but their use in hardware description languages is still limited. Moreover, tr

Exploring the Capability Boundaries of LLMs in Mastering of Chinese Chouxiang Language

model-releasesarxiv-cs-cl

arXiv:2604.15841v1 Announce Type: new Abstract: While large language models (LLMs) have achieved remarkable success in general language tasks, their performance on Chouxiang Language, a representative

Facial-Expression-Aware Prompting for Empathetic LLM Tutoring

arXiv:2604.15336v1 Announce Type: cross Abstract: Large language models (LLMs) enable increasingly capable tutoring-style conversational agents, yet effective tutoring requires sensitivity to learners

Factor Graph-Based Shape Estimation for Continuum Robots via Magnus Expansion

arXiv:2604.15619v1 Announce Type: new Abstract: Reconstructing the shape of continuum manipulators from sparse, noisy sensor data is a challenging task, owing to the infinite-dimensional nature of suc

researcharxiv-cs-ro

FACTS: Table Summarization via Offline Template Generation with Agentic Workflows

arXiv:2510.13920v2 Announce Type: replace Abstract: Query-focused table summarization requires generating natural language summaries of tabular data conditioned on a user query, enabling users to acce

agentsarxiv-cs-cl

Faithfulness-Aware Uncertainty Quantification for Fact-Checking the Output of Retrieval Augmented Generation

arXiv:2505.21072v4 Announce Type: replace Abstract: Large Language Models (LLMs) enhanced with retrieval, an approach known as Retrieval-Augmented Generation (RAG), have achieved strong performance in

researcharxiv-cs-cl

Faster LLM Inference via Sequential Monte Carlo

arXiv:2604.15672v1 Announce Type: cross Abstract: Speculative decoding (SD) accelerates language model inference by drafting tokens from a cheap proposal model and verifying them against an expensive

researcharxiv-cs-cl

FD-NL2SQL: Feedback-Driven Clinical NL2SQL that Improves with Use

arXiv:2604.15646v1 Announce Type: new Abstract: Clinicians exploring oncology trial repositories often need ad-hoc, multi-constraint queries over biomarkers, endpoints, interventions, and time, yet wr

researcharxiv-cs-cl

Fed3D: Federated 3D Object Detection

arXiv:2604.15795v1 Announce Type: new Abstract: 3D object detection models trained in one server plays an important role in autonomous driving, robotics manipulation, and augmented reality scenarios.

local-aiarxiv-cs-cv

Federated Learning with Quantum Enhanced LSTM for Applications in High Energy Physics

arXiv:2604.15775v1 Announce Type: new Abstract: Learning with large-scale datasets and information-critical applications, such as in High Energy Physics (HEP), demands highly complex, large-scale mode

local-aiarxiv-cs-lg

FETAL-GAUGE: A Benchmark for Assessing Vision-Language Models in Fetal Ultrasound

model-releasesarxiv-cs-cv

arXiv:2512.22278v2 Announce Type: replace Abstract: The growing demand for prenatal ultrasound imaging has intensified a global shortage of trained sonographers, creating barriers to essential fetal h

Find, Fix, Reason: Context Repair for Video Reasoning

arXiv:2604.16243v1 Announce Type: new Abstract: Reinforcement learning has advanced video reasoning in large multi-modal models, yet dominant pipelines either rely on on-policy self-exploration, which

safetyarxiv-cs-cv

FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation

model-releasesarxiv-cs-cv

arXiv:2604.16298v1 Announce Type: new Abstract: UAV vision-language navigation (VLN) requires an agent to navigate complex 3D environments from an egocentric perspective while following ambiguous mult

FineSteer: A Unified Framework for Fine-Grained Inference-Time Steering in Large Language Models

arXiv:2604.15488v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit undesirable behaviors, such as safety violations and hallucinations. Although inference-time steering offer

safetyarxiv-cs-ai

FL-MHSM: Spatially-adaptive Fusion and Ensemble Learning for Flood-Landslide Multi-Hazard Susceptibility Mapping at Regional Scale

arXiv:2604.16265v1 Announce Type: new Abstract: Existing multi-hazard susceptibility mapping (MHSM) studies often rely on spatially uniform models, treat hazards independently, and provide limited rep

researcharxiv-cs-lg

Flexible Empowerment at Reasoning with Extended Best-of-N Sampling

arXiv:2604.15614v1 Announce Type: new Abstract: This paper proposes a novel method that incorporates empowerment when reasoning actions in reinforcement learning (RL), thereby achieving the flexibilit

safetyarxiv-cs-lg

Follow the Flow: On Information Flow Across Textual Tokens in Text-to-Image Models

arXiv:2504.01137v3 Announce Type: replace Abstract: Text-to-image generation models suffer from alignment problems, where generated images fail to accurately capture the objects and relations in the t

safetyarxiv-cs-cl

Applications

Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions

arXiv:2604.15395v1 Announce Type: new Abstract: Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towa

applicationsarxiv-cs-ro