Renren Jin

According to our database1, Renren Jin authored at least 15 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons.
CoRR, 2024

ConTrans: Weak-to-Strong Alignment Engineering via Concept Transplantation.
CoRR, 2024

OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety.
CoRR, 2024

FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models.
CoRR, 2024

Do Large Language Models Mirror Cognitive Language Processing?
CoRR, 2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

LHMKE: A Large-scale Holistic Multi-subject Knowledge Evaluation Benchmark for Chinese Large Language Models.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

A Comprehensive Evaluation of Quantization Strategies for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models.
CoRR, 2023

Evaluating Large Language Models: A Comprehensive Survey.
CoRR, 2023

Large Language Model Alignment: A Survey.
CoRR, 2023

M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models.
CoRR, 2023

Joint Training and Decoding for Multilingual End-to-End Simultaneous Speech Translation.
Proceedings of the IEEE International Conference on Acoustics, 2023

CS2W: A Chinese Spoken-to-Written Style Conversion Dataset with Multiple Conversion Types.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Informative Language Representation Learning for Massively Multilingual Neural Machine Translation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022


  Loading...