Year | Venue | Tags | Paper Title | TL;DR | URL |
---|---|---|---|---|---|
2024 | EMNLP | Synthetic DataEvaluation | Second version of Prometheus | ||
2024 | NeurIPS | Synthetic DataEvaluation | Evaluation benchmark for Alignment | ||
2024 | ACL | Safety | Code Watermarking | ||
2024 | arXiv | Pre-trainingKorean NLPAlignmentEvaluationSafetySynthetic DataRL | Korean Foundation Model from Naver | ||
2024 | CHI | EvaluationHCI | Evaluation interface for LLM users | ||
2024 | ICLR | Synthetic DataEvaluation | Open-source LLM that is trained to evaluate LLM outputs | ||
2023 | EMNLP | Synthetic DataAlignment | Synthetic set of CoT data | ||
2023 | EMNLP | Synthetic DataAlignment | |||
2023 | EMNLP | Synthetic DataHCI | Synthetic approach to evaluate question generation quality of LLMs | ||
2023 | ACL | Synthetic Data | Synthetic Data approach to training DST models using LLMs | ||
2021 | NeurIPS | Korean NLPEvaluation | Comprehensive benchmark for Korean LLMs | ||
2020 | EMNLP | Korean NLP | |||
2020 | ICASSP | AlignmentRLSynthetic Data | Synthetic RLAIF approach to aligning LLMs with Empathy | ||
2019 | EMNLP | MoEAlignment | MoE models for Empathetic Alignment | ||
2019 | EMNLP | Korean NLPCross-linguality | Cross-lingual embeddings trained for Cross-lingual DST |