Search: “papers”

Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Rendering

arXiv:2604.27590v1 Announce Type: new Abstract: Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-rende

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FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving

DGX agent

arXiv:2604.02715v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models have become a dominant paradigm for scaling large language models, but their rapidly growing parameter sizes introdu

model-releasesarxiv-cs-lg

1 May 2026

Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation

arXiv:2510.20933v2 Announce Type: replace-cross Abstract: Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monit

Focus Session: Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification

arXiv:2604.27807v1 Announce Type: new Abstract: The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by

Foreclassing: A new machine learning perspective on human decision making with temporal data

arXiv:2503.04956v2 Announce Type: replace-cross Abstract: Time series forecasts are widely used to inform decisions. Human decision-makers interpret these forecasts, incorporate prior experience and u

applicationsarxiv-cs-lg

From Context to Skills: Can Language Models Learn from Context Skillfully?

arXiv:2604.27660v1 Announce Type: new Abstract: Many real-world tasks require language models (LMs) to reason over complex contexts that exceed their parametric knowledge. This calls for context learn

From LLM-Driven Trading Card Generation to Procedural Relatedness: A Pokemon Case Study

arXiv:2604.27972v1 Announce Type: new Abstract: Since the dawn of Trading Card Games, the genre has grown into a multi-billion-dollar industry engaging millions of analog and digital players worldwide

applicationsarxiv-cs-ai

From Unstructured Recall to Schema-Grounded Memory: Reliable AI Memory via Iterative, Schema-Aware Extraction

arXiv:2604.27906v1 Announce Type: new Abstract: Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant contex

From Unstructured to Structured: LLM-Guided Attribute Graphs for Entity Search and Ranking

arXiv:2604.27410v1 Announce Type: cross Abstract: Entity search, i.e., finding the most similar entities to a query entity, faces unique challenges in e-commerce, where product similarity varies acros

applicationsarxiv-cs-cl

Gait Recognition via Deep Residual Networks and Multi-Branch Feature Fusion

arXiv:2604.27353v1 Announce Type: new Abstract: Gait recognition has emerged as a compelling biometric modality for surveillance and security applications, offering inherent advantages such as non-int

GAVEL: Towards Rule-Based Safety Through Activation Monitoring

arXiv:2601.19768v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly paired with activation-based monitoring to detect and prevent harmful behaviors that may not be appare

Local Ai

Global Sampling-Based Trajectory Optimization for Contact-Rich Manipulation via KernelSOS

arXiv:2604.27175v1 Announce Type: new Abstract: Contact-rich manipulation is challenging due to its high dimensionality, the requirement for long time horizons, and the presence of hybrid contact dyna

local-aiarxiv-cs-ro

GourNet: A CNN-Based Model for Mango Leaf Disease Detection

arXiv:2604.27764v1 Announce Type: new Abstract: Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecti

applicationsarxiv-cs-cv

Tutorials

Graph World Models: Concepts, Taxonomy, and Future Directions

arXiv:2604.27895v1 Announce Type: new Abstract: As one of the mainstream models of artificial intelligence, world models allow agents to learn the representation of the environment for efficient predi

tutorialsarxiv-cs-ai

HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics

arXiv:2604.27542v1 Announce Type: new Abstract: Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal.

IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software Development

arXiv:2604.16399v2 Announce Type: replace-cross Abstract: The widespread adoption of AI-assisted development tools in 2025 -- and the emergence of vibe coding, a practice of generating complete applic

applicationsarxiv-cs-ai

In Line with Context: Repository-Level Code Generation via Context Inlining

arXiv:2601.00376v2 Announce Type: replace-cross Abstract: Repository-level code generation has attracted growing attention in recent years. Unlike function-level code generation, it requires the model

InterPartAbility: Text-Guided Part Matching for Interpretable Person Re-Identification

arXiv:2604.27122v1 Announce Type: new Abstract: Text-to-image person re-identification (TI-ReID) relies on natural-language text description to retrieve top matching individuals from a large gallery o

researcharxiv-cs-cv

Interval Orders, Biorders and Credibility-limited Belief Revision

arXiv:2604.27156v1 Announce Type: new Abstract: Rational belief revision is commonly viewed as being based on a preference order between possible worlds, with the resulting new belief set being those

Iterative Definition Refinement for Zero-Shot Classification via LLM-Based Semantic Prototype Optimization

arXiv:2604.27335v1 Announce Type: new Abstract: Web filtering systems rely on accurate web content classification to block cyber threats, prevent data exfiltration, and ensure compliance. However, cla

Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering

arXiv:2604.27724v1 Announce Type: new Abstract: Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual c

ITS-Mina: A Harris Hawks Optimization-Based All-MLP Framework with Iterative Refinement and External Attention for Multivariate Time Series Forecasting

arXiv:2604.27981v1 Announce Type: cross Abstract: Multivariate time series forecasting plays a pivotal role in numerous real-world applications, including financial analysis, energy management, and tr

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs 'Difficult' Downstream Tasks in LLMs

arXiv:2310.02277v4 Announce Type: replace-cross Abstract: We present Junk DNA Hypothesis by adopting a novel task-centric angle for the pre-trained weights of large language models (LLMs). It has been

KellyBench: A Benchmark for Long-Horizon Sequential Decision Making

arXiv:2604.27865v1 Announce Type: new Abstract: Language models are saturating benchmarks for procedural tasks with narrow objectives. But they are increasingly being deployed in long-horizon, non-sta

Knowledge Affordances for Hybrid Human-AI Information Seeking

arXiv:2604.27539v1 Announce Type: cross Abstract: As information ecosystems grow more heterogeneous, both humans and artificial agents increasingly face a simple yet unresolved question: when seeking

Knowledge Graph Representations for LLM-Based Policy Compliance Reasoning

arXiv:2604.27713v1 Announce Type: new Abstract: The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe

Language Ideologies in a Multilingual Society: An LLM-based Analysis of Luxembourgish News Comments

arXiv:2604.27661v1 Announce Type: new Abstract: Detecting language ideologies is a valuable yet complex task for understanding how identities are constructed through discourse. In Luxembourg's multicu

LaST-R1: Reinforcing Action via Adaptive Physical Latent Reasoning for VLA Models

arXiv:2604.28192v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have increasingly incorporated reasoning mechanisms for complex robotic manipulation. However, existing approaches

Leading Across the Spectrum of Human-AI Relationships: A Conceptual Framework for Increasingly Heterogeneous Teams

arXiv:2604.27392v1 Announce Type: new Abstract: What shapes a consequential decision when human and artificial intelligence work on it together? The answer is becoming harder to see. A decision may lo

Learning from a single labeled face and a stream of unlabeled data

arXiv:2604.27564v1 Announce Type: new Abstract: Face recognition from a single image per person is a challenging problem because the training sample is extremely small. We consider a variation of this

researcharxiv-cs-lg

Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies

arXiv:2604.27224v1 Announce Type: new Abstract: Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: visio

safetyarxiv-cs-ro

Learning-to-Explain through 20Q Gaming: An Explainable Recommender for Cybersecurity Education

arXiv:2604.26964v1 Announce Type: cross Abstract: The growing sophistication of contemporary cyber threats necessitates a more effective and adaptive approach to cybersecurity training. Intuitive and

Learning When to Remember: Risk-Sensitive Contextual Bandits for Abstention-Aware Memory Retrieval in LLM-Based Coding Agents

arXiv:2604.27283v1 Announce Type: cross Abstract: Large language model (LLM)-based coding agents increasingly rely on external memory to reuse prior debugging experience, repair traces, and repository

Leveraging Quantum-Based Architectures for Robust Diagnostics

arXiv:2511.12386v2 Announce Type: replace Abstract: Quantum machine learning has emerged as a promising approach for medical image analysis, particularly in settings where compact models and expressiv

researcharxiv-cs-cv

Low Rank Adaptation for Adversarial Perturbation

model-releasesarxiv-cs-lg

arXiv:2604.27487v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA), which leverages the insight that model updates typically reside in a low-dimensional space, has significantly improved the t

LUNA: LUT-Based Neural Architecture for Fast and Low-Cost Qubit Readout

arXiv:2512.07808v2 Announce Type: replace-cross Abstract: Qubit readout is a critical operation in quantum computing systems, which maps the analog response of qubits into discrete classical states. D

researcharxiv-cs-lg

Making Logic a First-Class Citizen in Generative ML for Networking

arXiv:2506.23964v3 Announce Type: replace-cross Abstract: Generative ML models are increasingly popular in networking for tasks such as telemetry imputation, prediction, and synthetic trace generation

applicationsarxiv-cs-lg

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

model-releasesarxiv-cs-lg

arXiv:2510.18183v2 Announce Type: replace Abstract: Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent

Normativity and Productivism: Ableist Intelligence? A Degrowth Analysis of AI Sign Language Translation Tools for Deaf People

arXiv:2604.28125v1 Announce Type: new Abstract: Sign languages, of any geographical or accentual variation, understandably face continuous scrutiny under the ever present popularity of verbal dictatio

On the Proper Treatment of Units in Surprisal Theory

arXiv:2604.28147v1 Announce Type: new Abstract: Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a uni

OpAgent: Operator Agent for Web Navigation

arXiv:2602.13559v2 Announce Type: replace Abstract: To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Convention

Optimization before Evaluation: Evaluation with Unoptimised Prompts Can be Misleading

arXiv:2604.27637v1 Announce Type: new Abstract: Current Large Language Model (LLM) evaluation frameworks utilize the same static prompt template across all models under evaluation. This differs from t

People-Centred Medical Image Analysis

arXiv:2604.26991v1 Announce Type: cross Abstract: Recent advances in data-centric medical AI have produced highly accurate diagnostic systems, but the emphasis on data curation and performance metrics

Local Ai

Policy-Governed LLM Routing with Intent Matching for Instrument Laboratories

arXiv:2604.26955v1 Announce Type: cross Abstract: AI tutoring systems in engineering labs face a tension between providing sufficient assistance and preserving learning opportunities. Existing systems

local-aiarxiv-cs-ai

Policy-Grounded Safety Evaluation of 20 Large Language Models

arXiv:2507.14719v2 Announce Type: replace Abstract: As large language models (LLMs) become increasingly integrated into real-world applications, scalable and rigorous safety evaluation is essential. T

Pragmos: A Process Agentic Modeling System

arXiv:2604.27311v1 Announce Type: cross Abstract: The advent of Large Language Models (LLMs) has significantly transformed tasks across Software Engineering. In the context of Business Process Managem

PVeRA: Probabilistic Vector-Based Random Matrix Adaptation

arXiv:2512.07703v2 Announce Type: replace Abstract: Large foundation models have emerged in the last years and are pushing performance boundaries for a variety of tasks. Training or even finetuning su

Qualitative Evaluation of Language Model Rescoring in Automatic Speech Recognition

arXiv:2604.27533v1 Announce Type: new Abstract: Evaluating automatic speech recognition (ASR) systems is a classical but difficult and still open problem, which often boils down to focusing only on th