Results for “accuracy”

Holistic evaluation framework for language models measuring accuracy, calibration, robustness, and fairness

Benchmarks zero-shot in-context learning on BIG-Bench Hard multiple-choice tasks, comparing self-generated demonstrations against direct prompting and chain-of-thought baselines, and reports accuracy.

Evaluates speech language models on beyond-semantic speech attributes such as dialect comprehension, multi-turn context memory, emotion perception, age-aware response generation, and non-verbal cue handling, reporting accuracy and judge-based scores.

编写评估FastText文本分类模型的Python函数，计算accuracy、F1、recall和precision指标，并处理特定格式的标签文本分割。

Validates data quality with completeness, consistency, accuracy checks and generates quality reports

QA a completed analysis for methodology, accuracy, and bias before it is shared, shipped, or acted on.

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.

Create medical coding guides for billing accuracy. TRIGGERS - Use when user needs help with coding-guide related tasks.

Create medical coding guides for billing accuracy. TRIGGERS - Use when user needs help with coding-guide related tasks.

Tightens existing copy for clarity, accuracy, tone consistency, and executive readability without altering the underlying message.

Produces high-quality written knowledge artifacts such as READMEs, guides, API specs, tutorials, runbooks, and wikis, with audience-appropriate structure and accuracy.

Registers a trading agent on zHive, fetches crypto signals, posts predictions with conviction, and competes for accuracy rewards.

Registers as a trading agent on zHive, fetches crypto signals, posts predictions with conviction, and competes for accuracy rewards.

Orchestrates a dimensional-analysis pipeline to annotate codebases with unit/dimension comments, discover dimensional vocabulary, and detect arithmetic bugs from unit mismatches or precision loss.

Use for writing, reviewing, debugging, testing, or validating Python mpmath arbitrary-precision numerical code. Trigger on mpf, mpc, mp.dps, workdps, interval arithmetic, high-precision quadrature, root finding, special functions, matrices, inverse transforms, or precision/convergence failures. Do not use for ordinary NumPy vectorization, SymPy symbolic manipulation, decimal currency arithmetic, or machine-float code with no precision requirement.

Improves AI skills for activation, clarity, and cross-model reliability through benchmarking, salience tuning, and regression triage.

Evaluates the correlation between automatic text generation scores and human quality ratings, including robustness to domain and quality drift, using metrics like Kendall's Tau and Pearson correlation.

Scores generated image captions against reference captions and source images using the Polos metric, which is trained to align with human judgments and probes hallucination robustness and open-vocabulary evaluation.

Quantifies the minimum accuracy gap needed between two models for a sampled micro-benchmark to reliably preserve their ranking, using the MDAD metric from Yauney et al. (2025).

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines

Data quality framework — completeness, accuracy, consistency, validation, and contracts. Use when implementing data validation, setting up quality checks for a pipeline, defining data contracts between teams, or investigating data anomalies.

Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

Improves measured performance while preserving correctness, reliability, and maintainability.

Creates data-driven infographics and charts as accessible SVG. Use when visualizing data, choosing a chart type, generating an SVG chart or infographic, or reviewing a visualization for clarity and accuracy.

Computes the SQuAD metric using torchmetrics, given predictions and ground truth. Use when evaluating question-answering outputs with exact match and F1 scores.

Socratic deep interview with mathematical ambiguity gating before explicit execution approval

Evaluates geometric consistency in text-to-video generation by measuring structural and motion coherence across camera trajectories, detecting deformation and occlusion artifacts in static scenes.

Computes CIDEr and related metrics to score how well generated image descriptions align with human consensus, using reference sentences and triplet annotations.