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15 results for "data quality"

ARXIV.ORG

MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation

The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scalable, while automate…

· 5 views
REDDIT

LabelSets — open quality standard for AI training data (LQS v3.1) [D]

Built a third-party quality rating system for ML datasets. Multi-oracle (7 scorers across 5 algorithm families), conformal prediction intervals on downstream F1, Ed25519-signed certs, and a contaminat…

· 8 views
DEV.TO (TOP)

Why Data Quality is Becoming More Important Than Model Size in Modern AI Systems

For years, progress in artificial intelligence was closely tied to scaling laws, where increasing...…

· 6 views
ARXIV CS.AI

ParkingScenes: A Structured Dataset for End-to-End Autonomous Parking in Simulation Scenes

Autonomous parking remains a critical yet challenging task in intelligent driving systems, particularly within constrained urban environments where maneuvering space is limited and precise control is …

· 4 views
ARXIV.ORG

Explanation Quality Assessment as Ranking with Listwise Rewards

We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single "best" explanation token-by-token, we train reward…

· 4 views
MARGINAL REVOLUTION

HUD Says Realtors Can Now Speak the Truth

HUD: The U.S. Department of Housing and Urban Development (HUD) sent a “Dear Colleague” letter to real estate professionals clarifying they are not violating the Fair Housing Act when they share infor…

· 4 views
MARGINAL REVOLUTION

HUD Says It’s Legal to Tell the Truth

HUD: The U.S. Department of Housing and Urban Development (HUD) sent a “Dear Colleague” letter to real estate professionals clarifying they are not violating the Fair Housing Act when they share infor…

· 4 views
LOCALLLAMA

Do the "*Claude-4.6-Opus-Reasoning-Distilled" really bring something new to the original models?

No offense to the fine-tune model providers, just curious. IMO the original models were already trained on massive amount of high quality data, so why bother with this fine-tune? Just to make the mode…

· 7 views
ARXIV.ORG

An Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement

Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This paper proposes an intelligent fault diagnosis frame…

· 4 views
ARXIV.ORG

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines

LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluation reliability. We present a comprehensive empir…

· 5 views
ARXIV.ORG

SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing

Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widely adopted in soccer refereeing, current AI-assis…

· 4 views
ARXIV.ORG

SemML 2.0: Synthesizing Controllers for LTL

Synthesizing a reactive system from specifications given in linear temporal logic (LTL) is a classical problem, finding its applications in safety-critical systems design. These systems are typically …

· 4 views
ARXIV.ORG

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of such…

· 4 views
ARXIV.ORG

A systematic evaluation of vision-language models for observational astronomical reasoning tasks

Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astronomical observations across diverse modalities r…

· 7 views
ARXIV.ORG

Microsoft TRELLIS.2: An Open-Source, 4B-Parameter, Image-to-3D Model [pdf]

Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, which struggle to capture assets with com…

· 5 views