Search: “benchmark”

arXiv:2609.22583v1 Announce Type: new Abstract: Predictive maintenance in Industry 4.0 refers to using data from sensors, machines, and production systems to estimate when equipment is likely to fail,

arXiv:2609.24190v1 Announce Type: new Abstract: Artificial intelligence (AI) has advanced at a rapid pace in recent years. Initially, breakthroughs in large language models caught widespread attention

arXiv:2609.23416v1 Announce Type: cross Abstract: Long-form audio performance is often summarized by context length and aggregate accuracy, obscuring how language, evidence, and task jointly shape dif

arXiv:2609.24064v1 Announce Type: new Abstract: New Guinea is the world's richest island flora (~2,856 orchid species), yet most species are represented by only a handful of photographs, far fewer tha

arXiv:2609.21490v1 Announce Type: new Abstract: Gender bias remains a persistent concern in machine translation (MT), affecting both generated translations and their automatic evaluation. When a sourc

arXiv:2609.21909v1 Announce Type: new Abstract: In this work, we conduct a systematic comparison of two state-of-the-art motion-imitation reinforcement learning (MIRL) pipelines, one built on SCONE/Hy

arXiv:2609.19965v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to legal and criminal justice tasks, yet existing work focuses almost exclusively on post-arrest s

arXiv:2609.20218v1 Announce Type: cross Abstract: Large language models can label a tabular row from a plain-English description with no training - a capability now shipping in mainstream spreadsheet

arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re

arXiv:2609.18406v1 Announce Type: new Abstract: Recovering 3D human body motion from video is important for applications such as rehabilitation assessment and sports performance evaluation. For prosth

arXiv:2609.16199v1 Announce Type: cross Abstract: This article describes an open image dataset for developing and evaluating active-fire segmentation methods in satellite imagery. The dataset contains

arXiv:2609.16777v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly serve as primary knowledge retrieval interfaces, their robustness against extit{persuasion attacks}---attem

arXiv:2609.16672v1 Announce Type: new Abstract: Background and Objective: Colonoscopy recording practice preserves text reports and still photographs, while the spatial information already present in

arXiv:2609.13072v1 Announce Type: cross Abstract: Fine-grained control of language model behaviors (e.g., steering) is among the more actionable outcomes of interpretability research. For binary conce

arXiv:2609.10801v1 Announce Type: new Abstract: Velocity-aware pitch control is standard, but under a broadcast viewport half the players are off screen and on-screen velocities come from a drifting c

arXiv:2609.03734v1 Announce Type: cross Abstract: BLEU-4 is the standard metric for evaluating sign language translation (SLT), but spoken-language metrics may not adequately reflect sign language pro

arXiv:2608.29286v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) evolve into sophisticated interactive assistants, their reliability depends not only on following instructio

arXiv:2608.28182v1 Announce Type: cross Abstract: Populations of large language model agents are increasingly used as experimental societies. Three doubts shadow every such result: whether the agents

arXiv:2608.26224v1 Announce Type: cross Abstract: Event triggering sits at the heart of high-energy physics, where the rare events of interest must be retained while an overwhelming background is disc

arXiv:2608.24934v1 Announce Type: new Abstract: Accurate field plant disease diagnosis requires reliable fusion of uncertain and conflicting perceptual evidence. We present the Hybrid Hierarchical Mul

arXiv:2601.17027v2 Announce Type: replace-cross Abstract: While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by t

arXiv:2608.23763v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as the standard layer connecting Large Language Model agents to external tool backends. This openness int

arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models

arXiv:2608.23095v1 Announce Type: new Abstract: Media bias detection relies on definitions and examples that specify what counts as bias, yet these specifications often vary across datasets or remain

arXiv:2608.21488v1 Announce Type: cross Abstract: While machine learning models have demonstrated strong performance in many domains, these models have shown profound vulnerabilities when they are exp

arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers

arXiv:2608.22331v1 Announce Type: new Abstract: We audit measurement variability for 3 native tool-calling endpoints across 2 providers on the official BFCL multiple and parallel categories, using mat

arXiv:2608.20362v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is a standard recipe for training large language models on mathematical reasoning, where an answer

arXiv:2608.21360v1 Announce Type: new Abstract: Recent omni-modal large language models (Omni-LLMs) show great potential as real-time video assistants, which continuously perceive environments and gui

arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval

arXiv:2608.17426v1 Announce Type: cross Abstract: We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formulation, success requires both achie

arXiv:2608.14778v1 Announce Type: new Abstract: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide, with early detection improving survival from 70%. The s

arXiv:2608.14976v1 Announce Type: new Abstract: Text-to-image models are typically reported on average-case prompts, which understates the gap between systems on compositionally demanding requests inv

arXiv:2608.15131v1 Announce Type: new Abstract: Digital platforms govern by changing rules: rankings, monetization thresholds, moderation standards, verification systems, disclosure requirements, appe

arXiv:2311.07073v3 Announce Type: replace Abstract: Graph-based message-passing neural networks (MPNNs) have achieved remarkable success in both node and graph-level learning tasks. However, several i

arXiv:2608.13511v1 Announce Type: new Abstract: Repeated in-situ evaluation of ocean-glider planners requires scarce vehicles, operators, deployment and recovery resources, and ocean conditions that c

arXiv:2506.17337v5 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown promise in automating image diagnosis and interpretation in clinical settings. However, developing sp

arXiv:2501.09700v2 Announce Type: replace-cross Abstract: Electroencephalogram (EEG) signals have emerged as a promising modality for biometric identification. While previous studies have explored the

arXiv:2602.10840v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely studied in areas such as mathematical reasoning, complex coding, and scientific problem solving. Howev

arXiv:2608.11423v1 Announce Type: cross Abstract: Robust comparisons of federated aggregation methods require joint consideration of predictive performance, threat definitions, metric semantics, and e

arXiv:2608.11981v1 Announce Type: new Abstract: Small Language Models (SLMs) have emerged as a more efficient alternative to traditional Large Language Models (LLMs), offering promising potential in r

arXiv:2608.10271v1 Announce Type: cross Abstract: Breast density classification is a critical component of breast cancer risk assessment, yet AI models often struggle to generalize across clinical sit

arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) mod

arXiv:2608.07822v1 Announce Type: cross Abstract: Quaternion-valued neural networks and variational quantum circuits (VQCs) both derive local transformations from SU(2) geometry, yet their performance

arXiv:2507.03162v2 Announce Type: replace-cross Abstract: The rapid advancement of Large Language Models (LLMs) has transformed various domains, particularly computer science (CS) education. These mod

arXiv:2511.11927v2 Announce Type: replace-cross Abstract: Principal Component Analysis (PCA) is a standard tool for extracting a low-rank signal from noisy observations. It is known that applying PCA