Search: “papers”

Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces

arXiv:2604.02832v2 Announce Type: replace-cross Abstract: Accurate forecasting of recovery rates (RR) is central to credit risk management and regulatory capital determination. In many loan portfolios

applicationsarxiv-cs-lg

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

Transferable Physics-Informed Representations via Closed-Form Head Adaptation

DGX agent

arXiv:2604.21761v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have garnered significant interest for their potential in solving partial differential equations (PDEs) that go

tutorialsarxiv-cs-lg

24 Apr 2026

Transformer-Progressive Mamba Network for Lightweight Image Super-Resolution

arXiv:2511.03232v2 Announce Type: replace Abstract: Recently, Mamba-based super-resolution (SR) methods have demonstrated the ability to capture global receptive fields with linear complexity, address

researcharxiv-cs-cv

Transient Turn Injection: Exposing Stateless Multi-Turn Vulnerabilities in Large Language Models

arXiv:2604.21860v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This pape

Trust but Verify: Introducing DAVinCI -- A Framework for Dual Attribution and Verification in Claim Inference for Language Models

arXiv:2604.21193v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable fluency and versatility across a wide range of NLP tasks, yet they remain prone to factual ina

applicationsarxiv-cs-ai

Unveiling Unicode's Unseen Underpinnings in Undermining Authorship Attribution

arXiv:2508.15840v5 Announce Type: replace-cross Abstract: When using a public communication channel--whether formal or informal, such as commenting or posting on social media--end users have no expect

agentsarxiv-cs-cl

Using ASP(Q) to Handle Inconsistent Prioritized Data

arXiv:2604.21603v1 Announce Type: cross Abstract: We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models

arXiv:2510.18457v3 Announce Type: replace Abstract: The performance of Latent Diffusion Models (LDMs) is critically dependent on the quality of their visual tokenizers. While recent works have explore

safetyarxiv-cs-cv

VistaBot: View-Robust Robot Manipulation via Spatiotemporal-Aware View Synthesis

model-releasesarxiv-cs-ro

arXiv:2604.21914v1 Announce Type: new Abstract: Recently, end-to-end robotic manipulation models have gained significant attention for their generalizability and scalability. However, they often suffe

Wiring the 'Why': A Unified Taxonomy and Survey of Abductive Reasoning in LLMs

arXiv:2604.08016v2 Announce Type: replace Abstract: Regardless of its foundational role in human discovery and sense-making, abductive reasoning--the inference of the most plausible explanation for an

Zero-Shot Detection of LLM-Generated Text via Implicit Reward Model

arXiv:2604.21223v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across various tasks. However, their ability to generate human-like text has ra

ZipFold: Modular Actuators for Scaleable Adaptive Robots

arXiv:2604.05260v2 Announce Type: replace Abstract: There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However,

researcharxiv-cs-ro

A Vision-Language-Action Model for Adaptive Ultrasound-Guided Needle Insertion and Needle Tracking

arXiv:2604.20347v1 Announce Type: cross Abstract: Ultrasound (US)-guided needle insertion is a critical yet challenging procedure due to dynamic imaging conditions and difficulties in needle visualiza

AI to Learn 2.0: A Deliverable-Oriented Governance Framework and Maturity Rubric for Opaque AI in Learning-Intensive Domains

arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs shoul

ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement

arXiv:2604.20721v1 Announce Type: new Abstract: Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and

researcharxiv-cs-ro

Aligning Stuttered-Speech Research with End-User Needs: Scoping Review, Survey, and Guidelines

arXiv:2604.20535v1 Announce Type: new Abstract: Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For

researcharxiv-cs-cl

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization

arXiv:2604.20748v1 Announce Type: new Abstract: Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although exist

applicationsarxiv-cs-cv

Analysis of Nystrom method with sequential ridge leverage scores

arXiv:2604.20077v1 Announce Type: new Abstract: Large-scale kernel ridge regression (KRR) is limited by the need to store a large kernel matrix K_t. To avoid storing the entire matrix K_t, Nystrom met

researcharxiv-cs-lg

AVISE: Framework for Evaluating the Security of AI Systems

arXiv:2604.20833v1 Announce Type: cross Abstract: As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-p

Avoiding Overthinking and Underthinking: Curriculum-Aware Budget Scheduling for LLMs

arXiv:2604.19780v1 Announce Type: new Abstract: Scaling test-time compute via extended reasoning has become a key paradigm for improving the capabilities of large language models (LLMs). However, exis

safetyarxiv-cs-cl

Beyond ZOH: Advanced Discretization Strategies for Vision Mamba

arXiv:2604.20606v1 Announce Type: cross Abstract: Vision Mamba, as a state space model (SSM), employs a zero-order hold (ZOH) discretization, which assumes that input signals remain constant between s

Bio-inspired Color Constancy: From Gray Anchoring Theory to Gray Pixel Methods

arXiv:2604.20243v1 Announce Type: new Abstract: Color constancy is a fundamental ability of many biological visual systems and a crucial step in computer imaging systems. Bio-inspired modeling offers

researcharxiv-cs-cv

CHASM: Unveiling Covert Advertisements on Chinese Social Media

arXiv:2604.20511v1 Announce Type: cross Abstract: Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements,

applicationsarxiv-cs-ai

CHORUS: An Agentic Framework for Generating Realistic Deliberation Data

arXiv:2604.20651v1 Announce Type: new Abstract: Understanding the intricate dynamics of online discourse depends on large-scale deliberation data, a resource that remains scarce across interactive web

agentsarxiv-cs-ai

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

Tutorials

Combo-Gait: Unified Transformer Framework for Multi-Modal Gait Recognition and Attribute Analysis

arXiv:2510.10417v2 Announce Type: replace-cross Abstract: Gait recognition is an important biometric for human identification at a distance, particularly under low-resolution or unconstrained environm

tutorialsarxiv-cs-ai

ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval

model-releasesarxiv-cs-cv

arXiv:2604.20358v1 Announce Type: new Abstract: The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on exp

Continuous Semantic Caching for Low-Cost LLM Serving

arXiv:2604.20021v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly popular, caching responses so that they can be reused by users with semantically similar queries h

applicationsarxiv-cs-cl

Cover meets Robbins while Betting on Bounded Data: ln n Regret and Almost Sure lnln n Regret

arXiv:2604.20172v1 Announce Type: new Abstract: Consider betting against a sequence of data in [0,1], where one is allowed to make any bet that is fair if the data have a conditional mean m_0 in (0,1)

researcharxiv-cs-lg

CubeDAgger: Interactive Imitation Learning for Dynamic Systems with Efficient yet Low-risk Interaction

arXiv:2505.04897v2 Announce Type: replace-cross Abstract: Interactive imitation learning makes an agent's control policy robust by stepwise supervisions from an expert. The recent algorithms mostly em

safetyarxiv-cs-lg

Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa

model-releasesarxiv-cs-cl

arXiv:2604.19776v1 Announce Type: new Abstract: Tuberculosis (TB) is one of the world's deadliest infectious diseases, and in South Africa, it contributes a significant burden to the country's health

Distributional Value Estimation Without Target Networks for Robust Quality-Diversity

arXiv:2604.20381v1 Announce Type: new Abstract: Quality-Diversity (QD) algorithms excel at discovering diverse repertoires of skills, but are hindered by poor sample efficiency and often require tens

researcharxiv-cs-lg

Do We Need Bigger Models for Science? Task-Aware Retrieval with Small Language Models

arXiv:2604.01965v2 Announce Type: replace-cross Abstract: Scientific knowledge discovery increasingly relies on large language models, yet many existing scholarly assistants depend on proprietary syst

Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

arXiv:2501.07399v2 Announce Type: replace Abstract: Consistent maps are key for most autonomous mobile robots, and they often use SLAM approaches to build such maps. Loop closures via place recognitio

safetyarxiv-cs-ro

Energy-Based Open-Set Active Learning for Object Classification

arXiv:2604.20083v1 Announce Type: cross Abstract: Active learning (AL) has emerged as a crucial methodology for minimizing labeling costs in deep learning by selecting the most valuable samples from a

applicationsarxiv-cs-cv

Enhancing Speaker Verification with Whispered Speech via Post-Processing

arXiv:2604.20229v1 Announce Type: cross Abstract: Speaker verification is a task of confirming an individual's identity through the analysis of their voice. Whispered speech differs from phonated spee

Epistemic Constitutionalism Or: how to avoid coherence bias

arXiv:2601.14295v3 Announce Type: replace Abstract: Large language models increasingly function as artificial reasoners: they evaluate arguments, assign credibility, and express confidence. Yet their

EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies

arXiv:2509.03335v3 Announce Type: replace Abstract: In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design

agentsarxiv-cs-lg

Fairness Testing of Large Language Models in Role-Playing

arXiv:2411.00585v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A cr

FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels

arXiv:2604.20825v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed client

Fextsuperscript{2}LP-AP: Fast & Flexible Label Propagation with Adaptive Propagation Kernel

model-releasesarxiv-cs-lg

arXiv:2604.20736v1 Announce Type: new Abstract: Semi-supervised node classification is a foundational task in graph machine learning, yet state-of-the-art Graph Neural Networks (GNNs) are hindered by

Finding Duplicates in 1.1M BDD Steps: cukereuse, a Paraphrase-Robust Static Detector for Cucumber and Gherkin

model-releasesarxiv-cs-cl

arXiv:2604.20462v1 Announce Type: cross Abstract: Behaviour-Driven Development (BDD) suites accumulate step-text duplication whose maintenance cost is established in prior work. Existing detection tec

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

arXiv:2603.09046v2 Announce Type: replace-cross Abstract: Device-side Large Language Models (LLMs) have witnessed explosive growth, offering higher privacy and availability compared to cloud-side LLMs

agentsarxiv-cs-lg

FLOSS: Federated Learning with Opt-Out and Straggler Support

arXiv:2507.23115v2 Announce Type: replace-cross Abstract: Previous work on data privacy in federated learning systems focuses on privacy-preserving operations for data from users who have agreed to sh

Tutorials

Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems

arXiv:2508.15411v3 Announce Type: replace-cross Abstract: Generative AI (GenAI) has emerged as a transformative technology, demonstrating remarkable capabilities across diverse application domains. Ho

tutorialsarxiv-cs-cl

From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents

arXiv:2604.19775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments.

agentsarxiv-cs-ai

From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP

arXiv:2510.12817v3 Announce Type: replace-cross Abstract: Human Label Variation (HLV) refers to legitimate disagreement in annotation that reflects the diversity of human perspectives rather than mere

From Scene to Object: Text-Guided Dual-Gaze Prediction

arXiv:2604.20191v1 Announce Type: cross Abstract: Interpretable driver attention prediction is crucial for human-like autonomous driving. However, existing datasets provide only scene-level global gaz