Knowledge catalogue
arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati
arXiv:2605.03919v1 Announce Type: cross Abstract: Reservoir geomodeling is central to subsurface characterization, but it remains challenging because conditioning data are sparse, geological heterogen
arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e
arXiv:2605.01359v1 Announce Type: new Abstract: In this paper, we employ the Minimal Cognitive Grid (MCG), a framework created to evaluate the cognitive plausibility of artificial systems, to offer a
The Structured Output Benchmark (SOB) dataset has been released and made available on Hugging Face. This dataset, hosted by Interfaze AI, likely provides benchmark data for evaluating models' ability
arXiv:2603.27343v2 Announce Type: replace Abstract: Existing large language models (LLMs) evaluations use fixed-difficulty benchmarks that cannot adapt as models improve, and rarely isolate specific c
arXiv:2605.01066v1 Announce Type: new Abstract: R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. Ho
arXiv:2605.02291v1 Announce Type: new Abstract: Video game engines have been an important source for generating large volumes of visual synthetic datasets for training and evaluating computer vision a
arXiv:2603.29895v2 Announce Type: replace-cross Abstract: We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how wel
arXiv:2510.18232v2 Announce Type: replace Abstract: Generating high-quality synthetic text under differential privacy (DP) is critical for training and evaluating language models without compromising
arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s
arXiv:2602.00074v2 Announce Type: replace-cross Abstract: While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with 'workflow friction' from manual da
arXiv:2605.02660v1 Announce Type: cross Abstract: Predicting microsatellite instability (MSI) status from routine hematoxylin and eosin (H&E) whole slide images (WSIs) offers a practical alternative t
arXiv:2605.01020v1 Announce Type: new Abstract: This paper proposes and evaluates a new performance estimation method that leverages continual learning (CL) algorithms to carry out sequential simulati
arXiv:2605.01371v1 Announce Type: new Abstract: The rapid advancement of Multimodal Large Language Models (MLLMs) has empowered Unmanned Aerial Vehicle (UAV) with exceptional capabilities in spatial r
arXiv:2603.09625v2 Announce Type: replace Abstract: Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However
Ethan Mollick advocates for dedicated funding toward developing independent benchmarking systems for AI models, noting that evaluation is currently predominantly conducted by the labs that create the
arXiv:2605.00904v1 Announce Type: new Abstract: Learning-based fluence map prediction offers a fast alternative to iterative inverse planning in intensity-modulated radiation therapy (IMRT), but its r
arXiv:2605.00382v2 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. Howeve
arXiv:2605.01452v1 Announce Type: cross Abstract: Existing evaluations of conformal prediction, such as prediction efficiency and test-conditional coverage, are defined in expectation over the calibra
arXiv:2601.08510v3 Announce Type: replace Abstract: Movie screenplays are rich long-form narratives that interleave complex character relationships, temporally ordered events, and dialogue-driven inte
arXiv:2605.02209v1 Announce Type: cross Abstract: Evaluating large language models across many benchmarks is expensive, yet many benchmarks are highly correlated. We formalize the selection of a small
arXiv:2504.20605v2 Announce Type: replace Abstract: Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives wi
arXiv:2605.02398v1 Announce Type: cross Abstract: As frontier AI models are deployed in high-stakes decision pipelines, their ability to maintain metacognitive stability -- knowing what they do not kn
arXiv:2603.26013v2 Announce Type: replace Abstract: Multilingual NLP is often treated as a route to global inclusion, but linguistic coverage and cultural competence frequently diverge. This paper syn
arXiv:2605.02223v1 Announce Type: cross Abstract: Recent advances in voice cloning and text-to-speech synthesis have made partial speech manipulation - where an adversary replaces a few words within a
arXiv:2605.00883v1 Announce Type: new Abstract: Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models
arXiv:2605.02834v1 Announce Type: new Abstract: Videos are unique in their ability to capture actions which transcend multiple frames. Accordingly, for many years action recognition was the quintessen
arXiv:2605.00508v1 Announce Type: new Abstract: We present a unique, multitask dataset comprising 143 drug and drug candidate molecules, each evaluated on in vitro, parallel artificial-membrane permea
arXiv:2605.00237v1 Announce Type: new Abstract: Bayesian optimization is a sequential method for minimizing objective functions that are expensive to evaluate and about which few assumptions can be ma
arXiv:2602.03265v2 Announce Type: replace Abstract: Large Language Models (LLMs) have seen widespread adoption across multiple domains, creating an urgent need for robust safety alignment mechanisms.
arXiv:2605.00119v1 Announce Type: new Abstract: There is a significant gap in evaluating cultural reasoning in LLMs using conversational datasets that capture culturally rich and dialectal contexts. M
arXiv:2605.00066v1 Announce Type: new Abstract: Open-loop evaluation offers fast, reproducible assessment of autonomous driving planners, but its ability to predict real closed-loop driving performanc
arXiv:2602.18757v2 Announce Type: replace Abstract: Human driving behavior is inherently diverse, yet most end-to-end autonomous driving (E2E-AD) systems learn a single average driving style, neglecti
Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evo
Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evo
Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evo
arXiv:2605.00760v1 Announce Type: new Abstract: This paper deals with solving the 2D Helmholtz equation on non-parametric domains, leveraging a physics-informed neural operator network based on the De
arXiv:2605.00764v1 Announce Type: new Abstract: Urban perception describes how people subjectively evaluate urban environments, shaping how cities are experienced and understood. Existing computationa
arXiv:2605.00062v1 Announce Type: cross Abstract: Rapid aerodynamic evaluation is crucial for modern vehicle design, yet existing neural operators struggle to capture intricate spatial correlations. W
arXiv:2512.19927v2 Announce Type: replace Abstract: Seismology faces fundamental challenges in state forecasting and reconstruction (e.g., earthquake early warning and ground motion prediction) and ma
arXiv:2605.00793v1 Announce Type: cross Abstract: With the development of deep learning, medical image processing has been widely used to assist clinical research. This paper focuses on the denoising
This post discusses self-review capabilities in AI systems, where an AI model can evaluate and refine its own outputs before presenting them to users. According to Florian Jue from Listen Labs, this f
arXiv:2605.00080v1 Announce Type: cross Abstract: World models, which are predictive representations of how environments evolve under actions, have become a central component of robot learning. They s
This post benchmarks three Qwen3.6 model variants against gpt-oss:120b when running on Apple Silicon hardware, evaluating their performance characteristics and practical usability. It documents both t
arXiv:2604.28078v1 Announce Type: new Abstract: Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors
arXiv:2602.11897v3 Announce Type: replace-cross Abstract: Cybersecurity decision-making increasingly occurs in environments characterized by uncertainty, partial observability, and adversarial manipul
arXiv:2604.26959v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into patient-facing healthcare systems offers significant potential to improve access to medical information.
arXiv:2604.28139v1 Announce Type: cross Abstract: LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks
arXiv:2604.27968v1 Announce Type: new Abstract: The pervasive growth of digital content, specifically short videos on social media platforms, has significantly altered how topics are discussed and und
arXiv:2604.27604v1 Announce Type: new Abstract: We introduce SPUR, a comprehensive benchmark for scientific experimental image perception, understanding, and reasoning, comprising 4,264 question-answe
arXiv:2604.27045v1 Announce Type: cross Abstract: As Large Language Model (LLM) agents transition from single-session tools to persistent systems managing longitudinal healthcare journeys, their memor
Tesla's official comparison tool allows customers to directly evaluate different Tesla vehicle models side-by-side, examining specifications, features, performance, and pricing to help inform purchase
arXiv:2506.02515v4 Announce Type: replace-cross Abstract: Multi-step symbolic reasoning is essential for robust financial analysis; yet, current benchmarks largely overlook this capability. Existing d
arXiv:2506.07180v3 Announce Type: replace-cross Abstract: As video large language models (Video-LLMs) become increasingly integrated into real-world applications that demand grounded multimodal reason
arXiv:2604.27557v1 Announce Type: new Abstract: Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting system
arXiv:2604.27186v1 Announce Type: cross Abstract: We study finite-horizon budget allocation as a closed-loop economic control problem and evaluate receding-horizon Model Predictive Control (MPC) relat
arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i
arXiv:2603.21016v2 Announce Type: replace-cross Abstract: Large language models (LLMs) used for multiple-choice and pairwise evaluation tasks often exhibit selection bias due to non-semantic factors l
arXiv:2507.03478v2 Announce Type: replace-cross Abstract: Image quality assessment (IQA) is crucial in the evaluation stage of novel algorithms operating on images, including traditional and machine l