Results for “scholar-evaluation”

Analyse student work against criteria to identify specific gaps between current performance and learning objectives. Use when reviewing submissions, planning feedback, or diagnosing learning needs.

Select evidence-based study strategies matched to material type, learning goal, and student habits. Use when advising students on revision techniques, homework, or independent study approaches.

Build students' capacity to interrogate a historical source before reading — asking who authored it, when, why, and what this means for reliability. Use when students read documents without attending to authorship.

Build students' capacity to read historical documents closely — attending to word choice, tone, and rhetoric as evidence of perspective. Use when students summarise sources without analysing language.

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.

Build students' capacity to compare accounts across multiple historical sources — identifying agreements, contradictions, and gaps. Use when students treat individual documents as complete answers rather than partial perspectives.

针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点，每道题互动问答、给出参考答案，复习结束后记录掌握进度，每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点，每道题互动问答、给出参考答案，复习结束后记录掌握进度，每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.

Analyse existing written feedback for quality, specificity, actionability, and impact on student learning. Use when reviewing teacher or peer feedback to improve feedback practices.

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.

The learner teaches the concept to the AI, which plays a curious novice peer and identifies gaps through authentic questions. Use when the learner wants to test their understanding — teaching forces a different kind of organisation than studying.

Validates the Emotional Attitude Score (EAS) metric by measuring its consistency with human judgment on word-level sentiment polarity, using the AmbGIMT dataset and pairwise score comparisons.