Shiwen Ni

Orcid: 0000-0002-4986-4446

According to our database1, Shiwen Ni authored at least 51 papers between 2020 and 2025.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2025
A Survey on Large Language Model Benchmarks.
CoRR, August, 2025

Expanding before Inferring: Enhancing Factuality in Large Language Models through Premature Layers Interpolation.
CoRR, June, 2025

Earley-Driven Dynamic Pruning for Efficient Structured Decoding.
CoRR, June, 2025

History, development, and principles of large language models: an introductory survey.
AI Ethics, June, 2025

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding.
CoRR, May, 2025

M-MRE: Extending the Mutual Reinforcement Effect to Multimodal Information Extraction.
CoRR, April, 2025

IPBench: Benchmarking the Knowledge of Large Language Models in Intellectual Property.
CoRR, April, 2025

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs.
CoRR, April, 2025

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.
CoRR, February, 2025

xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking.
CoRR, January, 2025

Distillation Quantification for Large Language Models.
CoRR, January, 2025

COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Pre-training, Fine-tuning and Re-ranking: A Three-Stage Framework for Legal Question Answering.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

LIME: Less Is More for MLLM Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Quantification of Large Language Model Distillation.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Can MLLMs Understand the Deep Implication Behind Chinese Images?
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Training on the Benchmark Is Not All You Need.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Masked Siamese Prompt Tuning for Few-Shot Natural Language Understanding.
IEEE Trans. Artif. Intell., February, 2024

EPRD: Exploiting prior knowledge for evidence-providing automatic rumor detection.
Neurocomputing, January, 2024

DropAttack: A Random Dropped Weight Attack Adversarial Training for Natural Language Understanding.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

Small Language Model as Data Prospector for Large Language Model.
CoRR, 2024

AutoPatent: A Multi-Agent Framework for Automatic Patent Generation.
CoRR, 2024

Can MLLMs Understand the Deep Implication Behind Chinese Images?
CoRR, 2024

LIME: Less Is More for MLLM Evaluation.
CoRR, 2024

Lower Layer Matters: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused.
CoRR, 2024

AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents.
CoRR, 2024

MMM: Multilingual Mutual Reinforcement Effect Mix Datasets & Test with Open-domain Information Extraction Large Language Models.
CoRR, 2024

II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models.
CoRR, 2024

COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning.
CoRR, 2024

MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property.
CoRR, 2024

History, Development, and Principles of Large Language Models-An Introductory Survey.
CoRR, 2024

Educational-Psychological Dialogue Robot Based on Multi-agent Collaboration.
Proceedings of the Social Robotics - 16th International Conference, 2024

II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Layer-wise Regularized Dropout for Neural Language Models.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

DeliLaw: A Chinese Legal Counselling System Based on a Large Language Model.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Forgetting before Learning: Utilizing Parametric Arithmetic for Knowledge Updating in Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

E-EVAL: A Comprehensive Chinese K-12 Education Evaluation Benchmark for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
KPT++: Refined knowledgeable prompt tuning for few-shot text classification.
Knowl. Based Syst., 2023

2022
HAT4RD: Hierarchical Adversarial Training for Rumor Detection in Social Media.
Sensors, 2022

ELECTRA is a Zero-Shot Learner, Too.
CoRR, 2022

R-AT: Regularized Adversarial Training for Natural Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
Rumor Detection on Social Media with Hierarchical Adversarial Training.
CoRR, 2021

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks.
CoRR, 2021

MVAN: Multi-View Attention Networks for Fake News Detection on Social Media.
IEEE Access, 2021

True or False: Does the Deep Learning Model Learn to Detect Rumors?
Proceedings of the 2021 International Conference on Technologies and Applications of Artificial Intelligence, 2021

Meet The Truth: Leverage Objective Facts and Subjective Views for Interpretable Rumor Detection.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020
Birds of a Feather Rumor Together? Exploring Homogeneity and Conversation Structure in Social Media for Rumor Detection.
IEEE Access, 2020

PSForest: Improving Deep Forest via Feature Pooling and Error Screening.
Proceedings of The 12th Asian Conference on Machine Learning, 2020


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