All entries

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

agentsarxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

End-to-End Learning for Partially-Observed Time Series with PyPOTS

DGX agent

arXiv:2604.24041v1 Announce Type: cross Abstract: Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from down

model-releasesarxiv-cs-ai

28 Apr 2026

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.24705v1 Announce Type: cross Abstract: Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy g

Energy-Aware Routing to Large Reasoning Models

arXiv:2601.00823v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it i

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy

arXiv:2604.23426v1 Announce Type: new Abstract: Federated learning (FL) is a distributed machine learning method where multiple devices collaboratively train a model under the management of a central

researcharxiv-cs-cv

Enhancing molecular dynamics with equivariant machine-learned densities

arXiv:2604.24563v1 Announce Type: cross Abstract: Machine-learning interatomic potentials (MLIPs) have enabled molecular dynamics at near ab initio accuracy, yet remain limited to energies and forces

Epicure: Multidimensional Flavor Structure in Food Ingredient Embeddings

arXiv:2604.22776v1 Announce Type: cross Abstract: A chef's intuition about flavor, texture, and cultural identity represents tacit knowledge that is difficult to articulate yet central to culinary pra

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Applications

Equivariant Filter for Radar-Inertial Odometry

arXiv:2604.23033v1 Announce Type: new Abstract: Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Meas

applicationsarxiv-cs-ro

Agents

Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization

arXiv:2604.23472v1 Announce Type: new Abstract: While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, i

agentsarxiv-cs-ai

Agents

ESIA: An Energy-Based Spatiotemporal Interaction-Aware Framework for Pedestrian Intention Prediction

arXiv:2604.23728v1 Announce Type: cross Abstract: Recent advances in autonomous driving have motivated research on pedestrian intention prediction, which aims to infer future crossing decisions and ac

agentsarxiv-cs-ai

Applications

ESPADA: Execution Speedup via Semantics Aware Demonstration Data Downsampling for Imitation Learning

arXiv:2512.07371v3 Announce Type: replace-cross Abstract: Behavior-cloning based visuomotor policies enable precise manipulation but often inherit the slow, cautious tempo of human demonstrations, lim

applicationsarxiv-cs-ai

Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach

model-releasesarxiv-cs-lg

arXiv:2601.18399v2 Announce Type: replace Abstract: Separating liquid-liquid dispersions in gravity settlers is critical in chemical, pharmaceutical, and recycling processes. The dense-packed zone hei

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

arXiv:2604.23466v1 Announce Type: cross Abstract: NVIDIA's CUDA Tile (CuTile) introduces a Python-based, tile-centric abstraction for GPU kernel development that aims to simplify programming while ret

Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

arXiv:2604.23341v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exp

Evaluating Language Models' Evaluations of Games

arXiv:2510.10930v2 Announce Type: replace-cross Abstract: Reasoning is not just about solving problems -- it is also about evaluating which problems are worth solving at all. Evaluations of artificial

Evaluating Large Language Models on Computer Science University Exams in Data Structures

arXiv:2604.23347v1 Announce Type: new Abstract: We present a comprehensive evaluation of Large Language Models (LLMs) on Computer Science (CS) Data Structure examination questions. Our work introduces

Evaluating Remote Sensing Image Captions Beyond Metric Biases

arXiv:2604.22855v1 Announce Type: new Abstract: The core objective of image captioning is to achieve lossless semantic compression from visual signals into textual modalities. However, the reliance on

researcharxiv-cs-cv

Evaluating Temporal Consistency in Multi-Turn Language Models

arXiv:2604.23051v1 Announce Type: new Abstract: Language models are increasingly deployed in interactive settings where users reason about facts over time rather than in isolation. In such scenarios,

Evaluating the Search Agent in a Parallel World

arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev

Evaluating whether AI models would sabotage AI safety research

arXiv:2604.24618v1 Announce Type: new Abstract: We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier

Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models

arXiv:2510.02629v3 Announce Type: replace Abstract: Context utilisation, the ability of Language Models (LMs) to incorporate relevant information from the provided context when generating responses, r

researcharxiv-cs-cl

Evaluation of Pose Estimation Systems for Sign Language Translation

arXiv:2604.24609v1 Announce Type: new Abstract: Many sign language translation (SLT) systems operate on pose sequences instead of raw video to reduce input dimensionality, improve portability, and par

researcharxiv-cs-cl

Evaluation of Prompt Injection Defenses in Large Language Models

arXiv:2604.23887v1 Announce Type: cross Abstract: LLM-powered applications routinely embed secrets in system prompts, yet models can be tricked into revealing them. We built an adaptive attacker that

Event-based SLAM Benchmark for High-Speed Maneuvers

model-releasesarxiv-cs-ro

arXiv:2604.24033v1 Announce Type: new Abstract: Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution,

Evolve: A Persistent Knowledge Lifecycle for Small Language Models

arXiv:2604.23424v1 Announce Type: cross Abstract: Evolve pairs a small local language model with a persistent, teacher-compiled knowledge store -- refined through sleep consolidation and usage-driven

EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment

model-releasesarxiv-cs-cv

arXiv:2604.22842v1 Announce Type: new Abstract: Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on fin

Local Ai

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin

local-aiarxiv-cs-cv

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

arXiv:2406.14075v2 Announce Type: replace Abstract: It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, financ

Applications

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task

arXiv:2604.23730v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capaci

applicationsarxiv-cs-ai

Tutorials

Explainable AI for Mental Disorder Detection via Social Media: A survey and outlook

arXiv:2406.05984v2 Announce Type: replace-cross Abstract: Mental health constitutes a complex and pervasive global challenge, affecting millions of lives and often leading to severe consequences. In t

tutorialsarxiv-cs-ai

Tutorials

Explainable AI in Speaker Recognition -- Making Latent Representations Understandable

arXiv:2604.23354v1 Announce Type: cross Abstract: Neural networks can be trained to learn task-relevant representations from data. Understanding how these networks make decisions falls within the Expl

tutorialsarxiv-cs-ai

Tutorials

Explainable Artificial Intelligence Techniques for Interpretation of Food Models: a Review

arXiv:2504.10527v2 Announce Type: replace Abstract: Artificial Intelligence (AI) has become essential for analyzing complex data and solving highly-challenging tasks. It is being applied across numero

tutorialsarxiv-cs-ai

Explaining Sources of Uncertainty in Automated Fact-Checking

arXiv:2505.17855v2 Announce Type: replace Abstract: Understanding sources of a model's uncertainty regarding its predictions is crucial for effective human-AI collaboration. Prior work proposes using

researcharxiv-cs-cl

Local Ai

Explaining Temporal Graph Predictions With Shapley Values

arXiv:2604.24078v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) have become increasingly popular in recent years due to their superior predictive performance by combining both s

local-aiarxiv-cs-lg

Explanation Quality Assessment as Ranking with Listwise Rewards

arXiv:2604.24176v1 Announce Type: new Abstract: We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single 'b

Explicit integral representations and quantitative bounds for two-layer ReLU networks

arXiv:2604.23260v1 Announce Type: cross Abstract: An approach to construct explicit integral representations for two-layer ReLU networks is presented, which provides relatively simple representations

Exploiting Differential Flatness for Efficient Learning-based Model Predictive Control of Constrained Multi-Input Control Affine Systems

arXiv:2604.24706v1 Announce Type: cross Abstract: Learning-based control techniques use data from past trajectories to control systems with uncertain dynamics. However, learning-based controllers are

Exploring Audio Hallucination in Egocentric Video Understanding

arXiv:2604.23860v1 Announce Type: cross Abstract: Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly whe

Exploring Hierarchical Consistency and Unbiased Objectness for Open-Vocabulary Object Detection

model-releasesarxiv-cs-cv

arXiv:2604.23344v1 Announce Type: new Abstract: Conventional object detectors typically operate under a closed-set assumption, limiting recognition to a predefined set of base classes seen during trai

Exploring the Impact of Dataset Statistical Effect Size on Model Performance and Data Sample Size Sufficiency

arXiv:2501.02673v4 Announce Type: replace Abstract: Having a sufficient quantity of quality data is a critical enabler of training effective machine learning models. Being able to effectively determin

Exploring the Secondary Risks of Large Language Models

arXiv:2506.12382v5 Announce Type: replace-cross Abstract: Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical application

Extending Precipitation Nowcasting Horizons via Spectral Fusion of Radar Observations and Foundation Model Priors

arXiv:2603.21768v3 Announce Type: replace-cross Abstract: Precipitation nowcasting is critical for disaster mitigation and aviation safety. However, radar-only models frequently suffer from a lack of

Extreme bandits

arXiv:2604.24545v1 Announce Type: cross Abstract: In many areas of medicine, security, and life sciences, we want to allocate limited resources to different sources in order to detect extreme values.

safetyarxiv-cs-lg

EyeBrain: Left and Right Brain Lateralization Activity Classification Through Pupil Diameter and Fixation Duration

arXiv:2604.23562v1 Announce Type: cross Abstract: The relationship between brain lateralization and cognitive functions is well-documented. The left hemisphere primarily handles tasks such as language

Local Ai

Factual and Edit-Sensitive Graph-to-Sequence Generation via Graph-Aware Adaptive Noising

arXiv:2604.24104v1 Announce Type: new Abstract: Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issu

local-aiarxiv-cs-cl

Failure-Centered Runtime Evaluation for Deployed Trilingual Public-Space Agents

arXiv:2604.23990v1 Announce Type: new Abstract: This paper presents PSA-Eval, a failure-centered runtime evaluation framework for deployed trilingual public-space agents. The central claim is that, wh

FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment

arXiv:2604.23786v1 Announce Type: new Abstract: In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental healt