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Ecologically-Constrained Task Arithmetic for Multi-Taxa Bioacoustic Classifiers Without Shared Data

arXiv:2605.03914v1 Announce Type: cross Abstract: Training data for bioacoustics is scattered across taxa, regions, and institutions. Centralizing it all is often infeasible. We show that independentl

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Research

Effect-Transparent Governance for AI Workflow Architectures: Semantic Preservation, Expressive Minimality, and Decidability Boundaries

DGX agent

arXiv:2605.01030v2 Announce Type: new Abstract: We present a machine-checked formalization of structurally governed AI workflow architectures and prove that effect-level governance can be imposed with

researcharxiv-cs-ai

6 May 2026

Effective Performance Measurement: Challenges and Opportunities in KPI Extraction from Earnings Calls

arXiv:2605.03147v1 Announce Type: new Abstract: Earnings calls are a key source of financial information about public companies. However, extracting information from these calls is difficult. Unlike t

Efficient Deconvolution in Populational Inverse Problems

arXiv:2505.19841v2 Announce Type: replace-cross Abstract: This work is focussed on the inversion task of inferring the distribution over parameters of interest leading to multiple sets of observations

Efficient Temporal Datalog Materialisation for Composite Event Recognition

arXiv:2605.02488v1 Announce Type: new Abstract: Several applications demand the timely detection of critical situations, such as threats to safety and transparency, over high-velocity streams of symbo

safetyarxiv-cs-ai

EFGPP: Exploratory framework for genotype-phenotype prediction

arXiv:2605.02954v1 Announce Type: cross Abstract: Predicting complex human traits from genetic data is challenging because different genetic, clinical, and molecular data sources often contain differe

ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity

arXiv:2605.03667v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable capabilities, but their immense computational demands during training remain a critical bottleneck

EMOVIS: Emotion-Optimized Image Processing

arXiv:2605.03131v1 Announce Type: cross Abstract: In cinematography, visual attributes such as color grading, contrast, and brightness are manipulated to reinforce the emotional narrative of a scene.

researcharxiv-cs-cv

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

arXiv:2510.12061v2 Announce Type: replace Abstract: Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generaliz

Agents

EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions

arXiv:2605.02289v1 Announce Type: new Abstract: Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but a

agentsarxiv-cs-ai

EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving

arXiv:2509.17677v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong performance on mathematical reasoning under well-defined conditions. However, real-world engineering

Tutorials

Enhance the after-discharge mortality rate prediction via learning from the medical notes

arXiv:2605.03560v1 Announce Type: new Abstract: With the increase of the Electronic Health Records (EHR) data, more and more researchers are developing machine learning models to learn from the medica

tutorialsarxiv-cs-lg

Enhanced 3D Brain Tumor Segmentation Using Assorted Precision Training

arXiv:2605.04008v1 Announce Type: new Abstract: A brain tumor is a medical disorder faced by individuals of all demographics. Medically, it is described as the spread of non-essential cells close to o

researcharxiv-cs-cv

Enhancing AI-Based ECG Delineation with Deep Learning Denoising Techniques

arXiv:2605.03183v1 Announce Type: new Abstract: Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinically relevant cardiac electrical activity. Common sources

Enhancing Self-Supervised Talking Head Forgery Detection via a Training-Free Dual-System Framework

arXiv:2605.03390v1 Announce Type: new Abstract: Supervised talking head forgery detection faces severe generalization challenges due to the continuous evolution of generators. By reducing reliance on

researcharxiv-cs-cv

Tutorials

Enhancing Visual Question Answering with Multimodal LLMs via Chain-of-Question Guided Retrieval-Augmented Generation

arXiv:2605.03790v1 Announce Type: new Abstract: With advances in multimodal research and deep learning, Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm for a wide range of

tutorialsarxiv-cs-cv

Entanglement is Half the Story: Post-Selection vs. Partial Traces

arXiv:2605.02385v1 Announce Type: cross Abstract: While tensor networks have their traditional application in simulating quantum systems, in the recent decade they have gathered interest as machine le

EO-Gym: A Multimodal, Interactive Environment for Earth Observation Agents

arXiv:2605.01250v1 Announce Type: new Abstract: Earth Observation (EO) analysis is inherently interactive: resolving uncertainty often requires expanding the region of interest, retrieving historical

eOptShrinkQ: Near-Lossless KV Cache Compression Through Optimal Spectral Denoising and Quantization

arXiv:2605.02905v1 Announce Type: new Abstract: We show that the key-value (KV) cache in transformer attention heads admits a natural decomposition into a low-rank shared context component and a full-

Epistemic Reject Option Prediction

arXiv:2511.04855v2 Announce Type: replace Abstract: In high-stakes applications, predictive models must not only produce accurate predictions but also quantify and communicate their uncertainty. Rejec

EQUITRIAGE: A Fairness Audit of Gender Bias in LLM-Based Emergency Department Triage

arXiv:2605.03998v1 Announce Type: new Abstract: Emergency department triage assigns patients an acuity score that determines treatment priority, and clinical evidence documents persistent gender dispa

Erase Persona, Forget Lore: Benchmarking Multimodal Copyright Unlearning in Large Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2605.03547v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs), trained on web-scale data, risk memorizing and regenerating copyrighted visual content such as characters and logo

Evaluating Agentic AI in the Wild: Failure Modes, Drift Patterns, and a Production Evaluation Framework

arXiv:2605.01604v1 Announce Type: new Abstract: Existing evaluation frameworks for large language models -- including HELM, MT-Bench, AgentBench, and BIG-bench -- are designed for controlled, single-s

Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior

arXiv:2605.03855v1 Announce Type: new Abstract: Human-AI collaboration requires AI agents to understand human behavior for effective coordination. While advances in foundation models show promising ca

researcharxiv-cs-ro

Evaluating Reasoning Models for Queries with Presuppositions

arXiv:2605.03050v1 Announce Type: new Abstract: Millions of users turn to AI models for their information needs. It is conceivable that a large number of user queries contain assumptions that may be f

researcharxiv-cs-cl

EvoJail: Evolutionary Diverse Jailbreak Prompt Generation for Large Language Models

arXiv:2605.02921v1 Announce Type: cross Abstract: As LLMs continue to shape real-world applications, automated jailbreak generation becomes essential to reveal safety weaknesses and guide model improv

safetyarxiv-cs-lg

Exact and Approximate Algorithms for Polytree Learning

arXiv:2605.03622v1 Announce Type: cross Abstract: Polytrees are a subclass of Bayesian networks that seek to capture the conditional dependencies between a set of n variables as a directed forest and

Exact ReLU realization of tensor-product refinement iterates

arXiv:2605.03917v1 Announce Type: cross Abstract: We study scalar dyadic refinement operators on R^2 of the form (Vf)(x,y) = sum_{(j,k) in Z^2} c_{j,k} f(2x-j, 2y-k), where only finitely many mask coe

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability

arXiv:2502.11336v2 Announce Type: replace Abstract: Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' acade

researcharxiv-cs-cl

Expanding functional protein sequence space using high entropy generative models

arXiv:2605.03578v1 Announce Type: cross Abstract: Boltzmann Machines trained on evolutionary sequence data have emerged as a powerful paradigm for the data-driven design of artificial proteins. Howeve

Agents

Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era

arXiv:2604.00187v2 Announce Type: replace-cross Abstract: Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual.

agentsarxiv-cs-ai

Exploring Pass-Rate Reward in Reinforcement Learning for Code Generation

arXiv:2605.02944v1 Announce Type: new Abstract: Reinforcement learning (RL) from unit-test feedback has become a standard post-training recipe for improving large language models (LLMs) on code genera

Exposing LLM Safety Gaps Through Mathematical Encoding:New Attacks and Systematic Analysis

arXiv:2605.03441v1 Announce Type: cross Abstract: Large language models (LLMs) employ safety mechanisms to prevent harmful outputs, yet these defenses primarily rely on semantic pattern matching. We s

FACTOR: Counterfactual Training-Free Test-Time Adaptation for Open-Vocabulary Object Detection

model-releasesarxiv-cs-cv

arXiv:2605.03294v1 Announce Type: new Abstract: Open-vocabulary object detection often fails under distribution shifts, as it can be misled by spurious correlations between non-causal visual attribute

Agents

Faithful Mobile GUI Agents with Guided Advantage Estimator

arXiv:2605.01208v1 Announce Type: new Abstract: Vision-language model based graphical user interface (GUI) agents have shown strong interaction capabilities. However, they often behave unfaithfully, r

agentsarxiv-cs-ai

False Friends in the Shell: Unveiling the Emoticon Semantic Confusion in Large Language Models

arXiv:2601.07885v2 Announce Type: replace-cross Abstract: Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs)

safetyarxiv-cs-ai

Feasibility-aware Hybrid Control for Motion Planning under Signal Temporal Logics

arXiv:2605.03662v1 Announce Type: new Abstract: In this work, a novel method for planar task and motion planning based on hybrid modeling is proposed. By virtue of a discrete variable which models loc

researcharxiv-cs-ro

Feature-Augmented Transformers for Robust AI-Text Detection Across Domains and Generators

arXiv:2605.03969v1 Announce Type: new Abstract: AI-generated text is nowadays produced at scale across domains and heterogeneous generation pipelines, making robustness to distribution shift a central

FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction

arXiv:2605.01726v1 Announce Type: cross Abstract: Sequential recommendation models often struggle to capture latent periodic patterns in user interests, primarily due to the noise inherent in time-dom

FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction

arXiv:2605.03425v1 Announce Type: new Abstract: Differentially private (DP) training protects individual examples by adding noise to gradients, but the injected noise interacts nontrivially with adapt

safetyarxiv-cs-lg

FINER-SQL: Boosting Small Language Models for Text-to-SQL

arXiv:2605.03465v1 Announce Type: cross Abstract: Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data

safetyarxiv-cs-cl

Finite-Size Gradient Transport in Large Language Model Pretraining: From Cascade Size to Intensive Transport Efficiency

arXiv:2605.02968v1 Announce Type: new Abstract: We introduce a finite-size gradient-transport framework for real language-model training, based on five observables (D,z,eta,elta,v_{rel}) that separate

FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models

arXiv:2605.03460v1 Announce Type: cross Abstract: Time series (TS) reasoning models (TSRMs) have shown promising capabilities in general domains, yet they consistently fail on financial domain, which

First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint

arXiv:2605.02827v1 Announce Type: new Abstract: Probabilistic values, including Shapley values and semivalues, provide a model-agnostic framework to attribute the behavior of a black-box model to data

Applications

First Shape, Then Meaning: Efficient Geometry and Semantics Learning for Indoor Reconstruction

arXiv:2605.03463v1 Announce Type: new Abstract: Neural Surface Reconstruction has become a standard methodology for indoor 3D reconstruction, with Signed Distance Functions (SDFs) proving particularly

applicationsarxiv-cs-cv

Flow Matching on Symmetric Spaces

arXiv:2605.03588v1 Announce Type: new Abstract: We introduce a general framework for training flow matching models on Riemannian symmetric spaces, a large class of manifolds that includes the sphere,

Tutorials

Flow Sampling: Learning to Sample from Unnormalized Densities via Denoising Conditional Processes

arXiv:2605.03984v1 Announce Type: new Abstract: Sampling from unnormalized densities is analogous to the generative modeling problem, but the target distribution is defined by a known energy function

tutorialsarxiv-cs-lg

FluxFlow: Conservative Flow-Matching for Astronomical Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2605.03749v1 Announce Type: new Abstract: Ground-to-space astronomical super-resolution requires recovering space-quality images from ground-based observations that are simultaneously limited by