PR-CAD unifies text-to-CAD generation and editing via progressive refinement with LLMs, a new interaction dataset, and RL-enhanced reasoning to achieve better controllability and faithfulness.
Llm-eval: Unified multi-dimensional automatic evaluation for open-domain conversations with large language models
8 Pith papers cite this work, alongside 13 external citations. Polarity classification is still indexing.
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representative citing papers
This systematic survey organizes prompt engineering into a taxonomy of 58 LLM techniques and 40 others, supplies a shared vocabulary, and offers guidelines for state-of-the-art models.
Poller reduces LLM-human disagreement in evaluating Chinese poetry understanding by having LLMs role-play as authors, with reported error reductions of 94.55% and 89.53% on rhetorical techniques and defamiliarization.
MDS selects better multi-turn dialogues for instruction tuning by combining bin-wise global coverage with local entity-topic and format consistency scoring, outperforming prior selectors on benchmarks.
OutSafe-Bench supplies the first large-scale four-modality safety dataset and evaluation framework that exposes persistent unsafe outputs in nine leading multimodal LLMs.
On binary verdicts, Pearson, Spearman, Kendall's tau-b, phi, and the Matthews correlation are a single statistic, so most multi-metric agreement reports repeat one number under different names.
The paper surveys the origins, frameworks, applications, and open challenges of AI agents built on large language models.
A survey that organizes LLMs-as-judges research into functionality, methodology, applications, meta-evaluation, and limitations.
citing papers explorer
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PR-CAD: Progressive Refinement for Unified Controllable and Faithful Text-to-CAD Generation with Large Language Models
PR-CAD unifies text-to-CAD generation and editing via progressive refinement with LLMs, a new interaction dataset, and RL-enhanced reasoning to achieve better controllability and faithfulness.
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The Prompt Report: A Systematic Survey of Prompt Engineering Techniques
This systematic survey organizes prompt engineering into a taxonomy of 58 LLM techniques and 40 others, supplies a shared vocabulary, and offers guidelines for state-of-the-art models.
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Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task?
Poller reduces LLM-human disagreement in evaluating Chinese poetry understanding by having LLMs role-play as authors, with reported error reductions of 94.55% and 89.53% on rhetorical techniques and defamiliarization.
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Data Selection for Multi-turn Dialogue Instruction Tuning
MDS selects better multi-turn dialogues for instruction tuning by combining bin-wise global coverage with local entity-topic and format consistency scoring, outperforming prior selectors on benchmarks.
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OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models
OutSafe-Bench supplies the first large-scale four-modality safety dataset and evaluation framework that exposes persistent unsafe outputs in nine leading multimodal LLMs.
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Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why
On binary verdicts, Pearson, Spearman, Kendall's tau-b, phi, and the Matthews correlation are a single statistic, so most multi-metric agreement reports repeat one number under different names.
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The Rise and Potential of Large Language Model Based Agents: A Survey
The paper surveys the origins, frameworks, applications, and open challenges of AI agents built on large language models.
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LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods
A survey that organizes LLMs-as-judges research into functionality, methodology, applications, meta-evaluation, and limitations.