Search: “papers”

SPECTRA-Net: Scalable Pipeline for Explainable Cross-domain Tensor Representations for AI-generated Images Detection

arXiv:2605.08226v1 Announce Type: new Abstract: The rapid proliferation of AI-generated images (AIGI) presents a significant challenge to digital information integrity. While human observers and exist

applicationsarxiv-cs-cv

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Speech-based Psychological Crisis Assessment using LLMs

DGX agent

arXiv:2605.10027v1 Announce Type: cross Abstract: Psychological support hotlines provide critical support for individuals experiencing mental health emergencies, yet current assessments largely rely o

researcharxiv-cs-ai

12 May 2026

Statistical Model Checking of the Keynes+Schumpeter Model: A Transient Sensitivity Analysis of a Macroeconomic ABM

arXiv:2605.10447v1 Announce Type: cross Abstract: Agent-based models (ABMs) are increasingly used in macroeconomics, but their analysis still often relies on ad hoc Monte Carlo campaigns with heteroge

Stellar Age Compression Reshapes Interpretations of the Milky Way Thick-Disk Formation History

arXiv:2605.10220v1 Announce Type: cross Abstract: The formation timescale of the Milky Way thick disk is one of the central debates in Galactic archaeology. The age-metallicity relation (AMR), formati

researcharxiv-cs-lg

Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review

arXiv:2605.08963v1 Announce Type: cross Abstract: Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore prim

safetyarxiv-cs-lg

Tabular Foundation Model for Generative Modelling

model-releasesarxiv-cs-lg

arXiv:2605.09424v1 Announce Type: new Abstract: Generative modelling is a demanding test of foundation models, because it requires robust, holistic representation learning for a given data modality, r

Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulation

model-releasesarxiv-cs-cl

arXiv:2505.11604v5 Announce Type: replace Abstract: Editing presentation slides is a frequent yet tedious task, ranging from creative layout design to repetitive text maintenance. While recent GUI-bas

Targeted Synthetic Control Method

arXiv:2602.04611v2 Announce Type: replace-cross Abstract: The synthetic control method (SCM) estimates causal effects in panel data with a single-treated unit by constructing a counterfactual outcome

safetyarxiv-cs-lg

Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning

model-releasesarxiv-cs-lg

arXiv:2605.10247v1 Announce Type: new Abstract: Using Large Language Models (LLMs) to process graph-structured data is an active research area, yet current state-of-the-art approaches typically rely o

Team-Based Self-Play With Dual Adaptive Weighting for Fine-Tuning LLMs

arXiv:2605.09922v1 Announce Type: cross Abstract: While recent self-training approaches have reduced reliance on human-labeled data for aligning LLMs, they still face critical limitations: (i) sensiti

Temporal-Decay Shapley: A Time-Aware Data Valuation Framework for Time-Series Data

arXiv:2605.08153v1 Announce Type: new Abstract: With the rapid development of machine learning applications on time-series data, accurately assessing the value of training samples has become essential

researcharxiv-cs-lg

Temporal Tokenization Strategies for Event Sequence Modeling with Large Language Models

arXiv:2512.13618v3 Announce Type: replace Abstract: Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Vari

applicationsarxiv-cs-cl

The Art of the Jailbreak: Formulating Jailbreak Attacks for LLM Security Beyond Binary Scoring

arXiv:2605.09225v1 Announce Type: cross Abstract: Jailbreak attacks -- adversarial prompts that bypass LLM alignment through purely linguistic manipulation -- pose a growing operational security threa

The Geometric Structure of Models Learning Sparse Data

arXiv:2605.08464v1 Announce Type: new Abstract: The manifold hypothesis (MH) is often used to explain how machine learning can overcome the curse of dimensionality. However, the MH is only applicable

safetyarxiv-cs-lg

The Impact of Editorial Intervention on Detecting Native Language Traces

arXiv:2605.10216v1 Announce Type: new Abstract: Native Language Identification (NLI) is the task of determining an author's native language (L1) from their non-native writings. With the advent of huma

researcharxiv-cs-cl

TIE: Time Interval Encoding for Video Generation over Events

arXiv:2605.10543v1 Announce Type: new Abstract: Director-style prompting, robotic action prediction, and interactive video agents demand temporal grounding over concurrent events -- a regime in which

safetyarxiv-cs-cv

TodyComm: Task-Oriented Dynamic Communication for Multi-Round LLM-based Multi-Agent System

arXiv:2602.03688v2 Announce Type: replace Abstract: Multi-round LLM-based multi-agent systems rely on effective communication structures to support collaboration across rounds. However, most existing

Top-H Decoding: Adapting the Creativity and Coherence with Bounded Entropy in Text Generation

arXiv:2509.02510v2 Announce Type: replace-cross Abstract: Large language models (LLMs), despite their impressive performance across a wide range of tasks, often struggle to balance two competing objec

Towards Autonomous Railway Operations: A Semi-Hierarchical Deep Reinforcement Learning Approach to the Vehicle Rescheduling Problem

arXiv:2605.10257v1 Announce Type: new Abstract: Managing disruptions in railway traffic management is a major challenge. Rising traffic density and infrastructure limits increase complexity, making th

Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models

arXiv:2605.09005v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) support generalist robotic control by enabling end-to-end decision policies directly from multi-modal inputs. As

Towards Generative Predictive Display for Vision-Based Teleoperation: A Zero-Shot Benchmark of Off-the-Shelf Video Models

model-releasesarxiv-cs-cv

arXiv:2605.09670v1 Announce Type: cross Abstract: Teleoperation systems are fundamentally limited by communication latency, which degrades situational awareness and control performance. Predictive dis

Towards Shutdownable Agents: Generalizing Stochastic Choice in RL Agents and LLMs

arXiv:2604.17502v2 Announce Type: replace Abstract: Misaligned artificial agents might resist shutdown. One proposed solution is to train agents to lack preferences between different-length trajectori

TRAM: Training Approximate Multiplier Structures for Low-Power AI Accelerators

arXiv:2605.08231v1 Announce Type: cross Abstract: Reducing power consumption in AI accelerators is increasingly important. Approximate computing can reduce power consumption while keeping the accuracy

Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression

arXiv:2605.08475v1 Announce Type: cross Abstract: Mechanistic accounts of in-context learning (ICL) have identified iterative algorithms for linear regression and related linear prediction tasks, ofte

UAV-Assisted Scan-to-Simulation for Landslides Using Physics-Informed Gaussian Splatting

arXiv:2605.10715v1 Announce Type: new Abstract: Landslide monitoring and simulation play an important role in urban safety assessment and disaster prevention. Existing landslide simulation pipelines t

safetyarxiv-cs-cv

Uncertainty-Aware and Decoder-Aligned Learning for Video Summarization

arXiv:2605.09507v1 Announce Type: new Abstract: Video summarization aims to produce a compact representation of a long video by selecting a subset of temporally important segments that best reflect hu

safetyarxiv-cs-cv

Unified Modeling of Lane and Lane Topology for Driving Scene Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.08911v1 Announce Type: new Abstract: Autonomous vehicles need to perceive not only physical elements in the driving scene, such as lane lines and traffic lights, but also logical elements l

Upholding Epistemic Agency: A Brouwerian Assertibility Constraint for Responsible AI

arXiv:2603.03971v2 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into hypersuasive, authoritative-seeming verdicts, displacing the justificatory work on which democratic

VAE with Hyperspherical Coordinates: Improving Anomaly Detection from Hypervolume-Compressed Latent Space

arXiv:2601.18823v3 Announce Type: replace Abstract: Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, one can h

applicationsarxiv-cs-lg

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations

arXiv:2605.08754v1 Announce Type: new Abstract: Taxiway routing and on-surface conflict avoidance are coupled safety-critical decision problems in airport surface operations. Existing planning and opt

ViSRA: A Video-based Spatial Reasoning Agent for Multi-modal Large Language Models

arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training

VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation

model-releasesarxiv-cs-ro

arXiv:2605.08886v1 Announce Type: cross Abstract: Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This

Visual Hand Gesture Recognition with Deep Learning: A Comprehensive Review of Methods, Datasets, Challenges and Future Research Directions

arXiv:2507.04465v4 Announce Type: replace Abstract: The rapid evolution of deep learning (DL) models and the ever-increasing size of available datasets have raised the interest of the research communi

researcharxiv-cs-cv

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning

arXiv:2605.08146v1 Announce Type: cross Abstract: Multi-model learning has attracted great attention in visual-text tasks. However, visual-tabular data, which plays a pivotal role in high-stakes domai

Weakly Supervised Concept Learning for Object-centric Visual Reasoning

arXiv:2605.08201v1 Announce Type: cross Abstract: Neurosymbolic systems promise to combine deep neural network's (DNN) processing of raw sensor inputs with few-shot performance of symbolic artificial

applicationsarxiv-cs-ai

What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook

arXiv:2605.08380v1 Announce Type: cross Abstract: AI agents are increasingly framed as software-engineering teammates, yet most research studies them inside human-centered workflows. Little is known a

When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning

arXiv:2605.09109v1 Announce Type: new Abstract: Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses s

When Child Inherits: Modeling and Exploiting Subagent Spawn in Multi-Agent Networks

arXiv:2605.08460v1 Announce Type: cross Abstract: Since the official release of ChatGPT in 2022, large language models (LLMs) have rapidly evolved from chatbot-style interfaces into agentic systems th

When Efficient Communication Explains Convexity

arXiv:2602.02821v2 Announce Type: replace Abstract: Much recent work has argued that the variation in the languages of the world can be explained from the perspective of efficient communication; in pa

researcharxiv-cs-cl

Tutorials

When Large Vision-Language Models Meet Person Re-Identification

arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un

tutorialsarxiv-cs-cv

Why Low-Resource NLP Needs More Than Cross-Lingual Transfer: Lessons Learned from Luxembourgish

arXiv:2605.10714v1 Announce Type: cross Abstract: Cross-lingual transfer has become a central paradigm for extending natural language processing (NLP) technologies to low-resource languages. By levera

Willful Disobedience: Automatically Detecting Failures in Agentic Traces

arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca

XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity

arXiv:2605.09639v1 Announce Type: cross Abstract: While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggre

researcharxiv-cs-cv

A Cost-Effective and Climate-Resilient Air Pressure System for Rain Effect Reduction on Automated Vehicle Cameras

arXiv:2602.17472v2 Announce Type: replace Abstract: Recent advances in automated vehicles have focused on improving perception performance under adverse weather conditions; however, research on physic

researcharxiv-cs-ro

A Reproducible Multi-Architecture Baseline for Token-Level Chinese Metaphor Identification under the MIPVU Framework

model-releasesarxiv-cs-cl

arXiv:2605.07170v1 Announce Type: new Abstract: Metaphor is pervasive in everyday language, yet token-level computational identification of metaphor-related words in Chinese under the MIPVU framework

A Self-Healing Framework for Reliable LLM-Based Autonomous Agents

arXiv:2605.06737v1 Announce Type: cross Abstract: Autonomous agents based on Large Language Models (LLMs) are increasingly being utilized in complex software systems. However, reliability remains a si

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence

arXiv:2605.06678v1 Announce Type: new Abstract: According to the United Nations Office for Disaster Risk Reduction (2025), the average annual cost of natural catastrophes increased from 70--80 billion

researcharxiv-cs-lg

Tutorials

Active teacher selection for reward learning

arXiv:2310.15288v3 Announce Type: replace Abstract: Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assu

tutorialsarxiv-cs-ai