Search: “benchmark”

arXiv:2604.11689v1 Announce Type: new Abstract: While the shortage of explicit action data limits Vision-Language-Action (VLA) models, human action videos offer a scalable yet unlabeled data source. A

arXiv:2604.10024v1 Announce Type: cross Abstract: Long video summarization presents significant challenges for current multimodal large language models (MLLMs), particularly in maintaining temporal fi

arXiv:2604.01306v2 Announce Type: replace Abstract: Evaluating scientific arguments requires assessing the strict consistency between a claim and its underlying multimodal evidence. However, existing

arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio

arXiv:2604.09678v1 Announce Type: cross Abstract: As agentic network management gains popularity, there is a critical need for evaluation frameworks that transcend static, one-shot testing. To address

arXiv:2604.10531v1 Announce Type: cross Abstract: Peptide therapeutics are widely regarded as the 'third generation' of drugs, yet progress in peptide Machine Learning (ML) are hindered by the absence

arXiv:2604.11711v1 Announce Type: new Abstract: Occlusion, where target structures are partially hidden by surgical instruments or overlapping tissues, remains a critical yet underexplored challenge f

arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i

arXiv:2604.09594v1 Announce Type: new Abstract: Spatial competence is the quality of maintaining a consistent internal representation of an environment and using it to infer discrete structure and pla

arXiv:2604.09574v1 Announce Type: new Abstract: The rise of autonomous GUI agents has triggered adversarial countermeasures from digital platforms, yet existing research prioritizes utility and robust

arXiv:2509.05215v3 Announce Type: replace Abstract: Recent works propose complex multi-modal models that handle both time series and language, ultimately claiming high performance on complex tasks lik

arXiv:2604.09151v1 Announce Type: new Abstract: Accurate segmentation of surgical instruments in robotic-assisted surgery is critical for enabling context-aware computer-assisted interventions, such a

arXiv:2511.23071v2 Announce Type: replace-cross Abstract: Reading scene text, that is, text appearing in images, has numerous application areas, including assistive technology, search, and e-commerce.

arXiv:2604.08987v1 Announce Type: new Abstract: As Large Language Models (LLMs) advance toward embodied AI agents operating in physical environments, a fundamental question emerges: can models trained

arXiv:2604.08570v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks

This r/ollama post describes a streamlined method for performance-testing locally-running large language models using the Ollama framework, achievable with just three terminal commands. It likely intr

arXiv:2604.06227v1 Announce Type: new Abstract: Accurate short-term forecasting of agricultural commodity prices is critical for food security planning and smallholder income stabilisation in developi

arXiv:2510.07927v2 Announce Type: replace Abstract: Anomaly detection plays a pivotal role in manufacturing quality control, yet its application is constrained by limited abnormal samples and high man

arXiv:2604.06188v1 Announce Type: cross Abstract: People increasingly hold sustained, open-ended conversations with large language models (LLMs). Public reports and early studies suggest that, in such

arXiv:2610.21555v1 Announce Type: cross Abstract: Muon's gains in data efficiency motivate evaluating its performance under explicit data, time, and tuning budgets. On a single A100 GPU, we compare a

arXiv:2610.15795v1 Announce Type: cross Abstract: Automated moderation systems are deployed at scale, yet they remain opaque to the users and moderators affected by their decisions, and their coverage

arXiv:2610.14807v1 Announce Type: new Abstract: Evaluating autonomous agents requires examining whether they can translate goals into coherent action across extended interactions. In persistent enviro

arXiv:2603.16557v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly store user preferences in persistent memory to support personalization across interactions. However,

arXiv:2610.16238v1 Announce Type: new Abstract: LLM agents increasingly control robots using VLA policies, perception models, and procedural knowledge. These modules are difficult to reuse because the

arXiv:2610.17722v1 Announce Type: cross Abstract: Quantum Machine Learning (QML) has a theoretical advantage over classical algorithms for specific synthetic data that is computationally hard. However

arXiv:2603.02475v2 Announce Type: replace Abstract: Skin tone classification is a fundamental task in computer vision, with applications in quantifying medical features, assessing demographic represen

arXiv:2610.18869v1 Announce Type: cross Abstract: How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning? We comp

arXiv:2610.12997v1 Announce Type: new Abstract: Prior-art retrieval systems are structurally organized around classification codes, making cross-code discovery difficult. This paper asks if an unsuper

arXiv:2610.13628v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies issue sparse targets whose arrival at the robot controller is delayed and irregular, so a reasonable predicted a

arXiv:2609.32396v2 Announce Type: replace Abstract: Forced alignment estimates the timestamps of each word, phone or character in speech given its transcript. Published comparisons normalize transcrip

arXiv:2610.10899v1 Announce Type: new Abstract: Speech quality predictors are increasingly used as rewards, yet no agreed measure of their hackability exists. The usual measurement has two flaws. Firs

arXiv:2610.12148v1 Announce Type: new Abstract: Quantum machine learning, and quantum neural networks (QNNs) in particular, are advancing fields with growing potential. Although systematic comparisons

arXiv:2610.06591v2 Announce Type: replace Abstract: How much of a conference accept/reject decision would change if the same paper were reviewed by a different set of reviewers? Running a second indep

arXiv:2610.10409v1 Announce Type: cross Abstract: General-purpose agents increasingly write code, use tools, and complete complex digital tasks, raising the question of how far these capabilities carr

arXiv:2610.08513v1 Announce Type: cross Abstract: LLMs are increasingly deployed as autonomous agents in social environments, making it critical to study their ability to faithfully simulate human int

arXiv:2610.06102v1 Announce Type: new Abstract: We investigate CLIP for zero-shot gender estimation from full-face and periocular images. Three CLIP backbones are evaluated on 11,299 frontal images fr

Purpose-built to stress-test computer vision models, depth cameras, and spatial AI against severe specular glare and geometric reflections. This 425-asset production archive features a custom faceted

Nonobench measures how well LLMs solve nonograms (picross). Each model gets the row and column clues once and returns the full grid. No tools, one attempt per puzzle. Method: - Standard mode: 30 puzzl

arXiv:2610.00833v1 Announce Type: cross Abstract: Fluent LLM explanations may not follow the evidence from a structured system. We present VERITYGATE, a four-gate checker for declared evidence IDs, en

arXiv:2609.39257v1 Announce Type: cross Abstract: Accurate forecasting of electricity production is essential for maintaining the operational efficiency and strategic planning of energy utilities. In

arXiv:1806.11314v3 Announce Type: replace Abstract: Many works have been done on salient object detection using supervised or unsupervised approaches on colour images. Recently, a few studies demonstr

arXiv:2609.38460v1 Announce Type: new Abstract: Language agents must revise planned actions when evidence changes, permission is revoked, or a stop instruction arrives. A useful response is selective:

arXiv:2609.37853v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as social agents, yet credible human-like interaction requires more than fluent responses or pers

arXiv:2609.37647v1 Announce Type: cross Abstract: Jev is a commercial System One model from TypeSafe AI that does not generate text: given a state and typed questions, it returns a choice from fixed o

arXiv:2609.35965v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require te

arXiv:2609.31665v1 Announce Type: new Abstract: Action anticipation predicts future human actions from partial video under incomplete context and temporal uncertainty. Recent systems introduce large l