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Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR

arXiv:2605.29637v1 Announce Type: new Abstract: Large language models recall knowledge reliably in English but often fail on the same query posed in a lower-resourced language -- a crosslingual consis

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Evaluating Dataset Watermarking for Fine-tuning Traceability of Customized Diffusion Models: A Comprehensive Benchmark and Removal Approach

DGX agent

arXiv:2511.19316v2 Announce Type: replace-cross Abstract: Recent fine-tuning techniques for diffusion models enable them to reproduce specific image sets, such as particular faces or artistic styles,

model-releasesarxiv-cs-ai

29 May 2026

Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations

arXiv:2605.29976v1 Announce Type: cross Abstract: We evaluate the climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather fore

Evaluation of Conversational Agents: Understanding Culture, Context and Environment in Emotion Detection

arXiv:2605.30099v1 Announce Type: new Abstract: Valuable decisions and highly prioritized analysis now depend on applications such as facial biometrics, social media photo tagging, and human robots in

applicationsarxiv-cs-cv

EviLink: Multi-Path Schema Linking with Uncertainty-Guided Evidence Acquisition for Large-Scale Text-to-SQL

arXiv:2605.29670v1 Announce Type: cross Abstract: Schema linking is a difficult and important step in large-scale Text-to-SQL, where systems must identify a compact yet sufficient schema context from

EVL-ECG: Efficient ECG Interpretation With Multi-Aspect Heterogeneous Knowledge Distillation

model-releasesarxiv-cs-cv

arXiv:2605.29977v1 Announce Type: new Abstract: High-fidelity ECG interpretation is increasingly reliant on massive foundation models, yet their deployment in clinical edge-care remains hindered by ex

Evolutionary Dynamics of Cooperation in Next-Generation LLM Agent Systems: A Cross-Provider Empirical Extension

arXiv:2605.29874v1 Announce Type: cross Abstract: Do next-generation LLM agents inherit the cooperative biases documented in their predecessors, or does scale and provider diversity reshape equilibriu

Evolutionary Refinement of Generative Graph Topologies: A Hybrid WGAN-GA Approach

arXiv:2605.29161v1 Announce Type: cross Abstract: Generating realistic graph-structured data is challenging due to discrete connectivity, varying graph sizes, and class-specific structural patterns. R

safetyarxiv-cs-ai

Evolutionary Rule Extraction from Corporate Default Prediction Models

arXiv:2605.29478v1 Announce Type: cross Abstract: Small and medium-sized enterprises (SMEs) represent the majority of firms in most economies and often face financial constraints and higher vulnerabil

Agents

Evolve as a Team: Collaborative Self-Evolution for LLM-based Multi-Agent Systems

arXiv:2605.29790v1 Announce Type: cross Abstract: LLM-based multi-agent systems (MAS) have emerged as an effective paradigm for complex and long-horizon tasks. However, in real-world tasks, MAS often

agentsarxiv-cs-ai

Evolving Features vs Evolving Entire Trees with GP for Interpretable Survival Analysis

arXiv:2605.30119v1 Announce Type: cross Abstract: Survival analysis concerns the task of predicting the time until an event occurs. Often used in the medical field, survival analysis deals with incomp

applicationsarxiv-cs-ai

EvoMD-LLM: Learning the Language of Species Evolution in Reactive Molecular Dynamics

arXiv:2605.29394v1 Announce Type: new Abstract: While large language models (LLMs) excel at static scientific reasoning, they struggle to model the temporal structure of dynamic physical processes. We

safetyarxiv-cs-ai

EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation

arXiv:2605.29847v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly advanced Large Language Models (LLMs) in verifiable domains, but aligning models for open-ended generation

safetyarxiv-cs-cl

EXACT-MPPI: Exact Signed-Distance Navigation for Arbitrary-Footprint Robots from Point Clouds via Path Integral Control

arXiv:2605.29663v1 Announce Type: new Abstract: Ground robots often carry payloads, implements, or other attachments that turn their effective footprint into complex, non-convex shapes. Navigating saf

local-aiarxiv-cs-ro

ExCAM: Explainable Cultural Awareness Metrics

arXiv:2605.29897v1 Announce Type: new Abstract: Evaluating the cultural awareness of large language models is crucial to ensure the fairness of generated text and the generalizability of applications

ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material

arXiv:2605.30225v1 Announce Type: new Abstract: Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they

researcharxiv-cs-lg

Explaining Concept Shift with Interpretable Feature Attribution

arXiv:2505.20634v2 Announce Type: replace Abstract: Concept shift occurs when the distribution of labels conditioned on the features changes between domains, which can make even a well-tuned ML model

Extreme dynamic symmetry enables omnidirectional and multifunctional robots

arXiv:2605.29254v1 Announce Type: cross Abstract: Symmetry is a central organizing principle in natural systems, yet its use as a unifying design strategy in robotics has largely remained limited to g

F-RNG: Feed-Forward Relightable Neural Gaussians

arXiv:2605.25975v2 Announce Type: replace-cross Abstract: Capturing relightable 3D assets from real-world objects is a widely researched problem. Several per-scene optimization-based methods, based on

applicationsarxiv-cs-cv

Fairness-Aware Federated Learning with Trajectory Shapley Value

arXiv:2605.30336v1 Announce Type: new Abstract: Federated learning is an emerging distributed paradigm that addresses the challenges posed by heterogeneous, privacy-sensitive data. It enables multiple

Fairness Beyond Demographics: Optimizing Performance Across Appearance-Based Hidden Cohorts in Medical Imaging

model-releasesarxiv-cs-cv

arXiv:2605.29827v1 Announce Type: new Abstract: Medical image analysis models can exhibit performance disparities across patient subgroups, threatening clinical safety and fairness. Existing methods t

Faithful Embeddings of Irregular and Asynchronous Data for Online Log-NCDEs

arXiv:2605.30213v1 Announce Type: new Abstract: Continuous-time models are a natural choice for irregular and asynchronous data. A central design choice is how to embed discrete observations into cont

FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection

arXiv:2605.30062v1 Announce Type: new Abstract: The development of generative artificial intelligence technologies has propelled the visual realism of synthetic images to an unprecedented level. Altho

safetyarxiv-cs-cv

FarSkip-Collective: Unhobbling Blocking Communication in Mixture of Experts Models

arXiv:2511.11505v3 Announce Type: replace Abstract: Blocking communication presents a major hurdle in running MoEs efficiently in distributed settings. To address this, we present FarSkip-Collective w

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces

arXiv:2602.14975v3 Announce Type: replace-cross Abstract: Following our previous work (J. Phys. Chem. Lett., 2026, 17, 5, 1288-1295), we propose the DMTS-NC approach, a distilled multi-time-step (DMTS

applicationsarxiv-cs-lg

Feature Geometry of LoRA Adapters: A Sparse Autoencoder Analysis of Representational Divergence in Fine-Tuned Language Models

arXiv:2605.28896v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has emerged as a widely adopted approach for adapting large language models, yet the internal representational changes induce

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning

arXiv:2605.29002v1 Announce Type: new Abstract: Federated reinforcement learning enables decentralized agents to collaboratively improve policies or value estimates without exchanging raw trajectories

FedSmoothLoRA: Toward Smoother and Faster Convergence in Federated Low-Rank Adaptation

arXiv:2605.29460v1 Announce Type: new Abstract: Federated fine-tuning of foundation models with Low-Rank Adaptation (LoRA) provides an efficient solution for reducing communication and computation cos

local-aiarxiv-cs-cv

Feedback-to-Rubrics: Can We Learn Expert Criteria from Inline Comments?

arXiv:2605.29857v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for writing and review support, but their usefulness depends on context-dependent criteria, such as e

Fewer Steps, Better Performance: Efficient Cross-Modal Clip Trimming for Video Moment Retrieval Using Language

arXiv:2605.29793v1 Announce Type: new Abstract: Given an untrimmed video and a sentence query, video moment retrieval using language (VMR) aims to locate a target query-relevant moment. Since the untr

safetyarxiv-cs-cv

FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting

arXiv:2605.29695v1 Announce Type: new Abstract: Approximately 10% of newborns require assistance to initiate breathing at birth, and around 5% need ventilation support. Fetal heart rate (FHR) monitori

local-aiarxiv-cs-ai

Financially Guided Deep Portfolio Optimization

arXiv:2605.28853v1 Announce Type: cross Abstract: Portfolio optimization in real-world financial markets is notoriously difficult due to non-stationarity, noisy data, and high transaction costs. Stand

Finding DoRI: Discovery of Retained Images in Diffusion Models

arXiv:2507.16880v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models (DMs) have achieved remarkable success in image generation. However, concerns about data privacy and intellectu

local-aiarxiv-cs-ai

Fingerprinting Inference Systems of Large Language Models

arXiv:2605.29979v1 Announce Type: cross Abstract: The behavior of LLMs does not depend solely on the model itself. Components of the inference system, such as the inference engine, attention backend,

researcharxiv-cs-lg

FinGuard: Detecting Financial Regulatory Non-Compliance in LLM Interactions

arXiv:2605.29427v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed in financial services, a single non-compliant interaction can expose institutions to regulator

FinVerBench: Benchmark Validity and Calibration in Large Language Model Financial Statement Verification

arXiv:2605.29586v1 Announce Type: new Abstract: We introduce FinVerBench, a benchmark and validity study for financial statement verification: determining whether a set of corporate financial statemen

First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope

arXiv:2605.28916v1 Announce Type: cross Abstract: We report a comparison of two state-of-the-art agentic AI systems, Claude Code (Anthropic) and Codex (OpenAI), tasked with autonomously executing a si

Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control

arXiv:2605.29937v1 Announce Type: cross Abstract: Diffusion models are effective for waypoint prediction in visual navigation, but standard sampling and test time guidance can produce unreliable or in

safetyarxiv-cs-lg

Agents

FLIP: Real-Time and Resilient Formation Planning for Large-Scale DIstributed Swarms via Point Cloud Registration

arXiv:2605.29704v1 Announce Type: new Abstract: Traditional large-scale formation planning either oversimplify the formation representation which leads to poor performance, or they employ complete col

agentsarxiv-cs-ro

FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation

arXiv:2605.29461v1 Announce Type: new Abstract: LLM-conditioned segmentation has recently advanced rapidly by coupling large language models with iterative mask generation frameworks. However, we iden

safetyarxiv-cs-cv

Follow Everything: A Leader-Following and Obstacle Avoidance Framework with Goal-Aware Adaptation

arXiv:2504.19399v4 Announce Type: replace Abstract: Robust and flexible leader-following is a critical capability for robots to integrate into human society. While existing methods struggle to general

applicationsarxiv-cs-ro

Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality

arXiv:2510.12152v2 Announce Type: replace-cross Abstract: We study the decoupled multi-armed bandit problem, where the learner separately selects one arm for exploration and one, possibly different, a

safetyarxiv-cs-lg

FoRA: Fisher-orthogonal Rank Adaptation for Parameter-Efficient Fine-Tuning

arXiv:2605.29317v1 Announce Type: new Abstract: Parameter-efficient fine-tuning(PEFT) has largely focused on LoRA and its accuracy-oriented variants, leaving the original goal of reducing trainable pa

Force Sensing for Wearable Human-Robot Interfaces via Fluidic Innervation

arXiv:2602.13436v2 Announce Type: replace Abstract: Mechanically characterizing the human-machine interface is essential to understanding user behavior and optimizing wearable robot performance. This

applicationsarxiv-cs-ro

Forget Less, Generalize More: Unifying Temporal and Structural Adaptation for Dynamic Graphs

arXiv:2605.29453v1 Announce Type: cross Abstract: Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typi

applicationsarxiv-cs-ai

FormalEvolve: Neuro-Symbolic Evolutionary Search for Diverse Autoformalization

arXiv:2603.19828v3 Announce Type: replace Abstract: Autoformalization aims to produce formal statements that compile and faithfully preserve the intended meaning of informal mathematics. Yet standard

Agents

Formalizing Mathematics at Scale

arXiv:2605.29955v1 Announce Type: new Abstract: We present AutoformBot, a multi-agent system for building an Autoformalized Textbook Library At Scale (Atlas) in Lean 4. AutoformBot orchestrates thousa

agentsarxiv-cs-ai

FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks

arXiv:2605.29001v1 Announce Type: cross Abstract: A paraphrase-quality audit of MathCheck (ICLR 2025) detected 4 semantically incorrect paraphrases in 129 groups (3.1%); removing them drops GPT-4o fro