Tingchen Fu

Orcid: 0000-0003-3692-729X

According to our database1, Tingchen Fu authored at least 16 papers between 2022 and 2024.

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

Timeline

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Bibliography

2024
PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning.
CoRR, 2024

Unlocking Decoding-time Controllability: Gradient-Free Multi-Objective Alignment with Contrastive Prompts.
CoRR, 2024

On the Transformations across Reward Model, Parameter Update, and In-Context Prompt.
CoRR, 2024

The Reasonableness Behind Unreasonable Translation Capability of Large Language Model.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Disperse-Then-Merge: Pushing the Limits of Instruction Tuning via Alignment Tax Reduction.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.
CoRR, 2023

Delving into Global Dialogue Structures: Structure Planning Augmented Response Selection for Multi-turn Conversations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Logic Unveils Truth, While Disguise Obscures It: Transition Logic Augmented Response Selection for Multi-Turn Dialogue.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SORTIE: Dependency-Aware Symbolic Reasoning for Logical Data-to-text Generation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

On the Compositional Generalization in Versatile Open-domain Dialogue.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Learning towards conversational AI: A survey.
AI Open, January, 2022

Learning to Express in Knowledge-Grounded Conversation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Towards Efficient Dialogue Pre-training with Transferable and Interpretable Latent Structure.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

There Is No Standard Answer: Knowledge-Grounded Dialogue Generation with Adversarial Activated Multi-Reference Learning.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

There Are a Thousand Hamlets in a Thousand People's Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022


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