Anningzhe Gao

According to our database1, Anningzhe Gao authored at least 26 papers between 2023 and 2025.

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

Timeline

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Bibliography

2025
Prototype-Oriented Clean Subset Extraction for Noisy Long-Tailed Classification.
IEEE Trans. Circuits Syst. Video Technol., August, 2025

Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm.
CoRR, March, 2025

Simplify RLHF as Reward-Weighted SFT: A Variational Method.
CoRR, February, 2025

Synthesizing Minority Samples for Long-tailed Classification via Distribution Matching.
Trans. Mach. Learn. Res., 2025

Huatuo-26M, a Large-scale Chinese Medical QA Dataset.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural and Mathematical Languages.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Atoxia: Red-teaming Large Language Models with Target Toxic Answers.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Unlocking LLMs' Self-Improvement Capacity with Autonomous Learning for Domain Adaptation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

Aligning Language Models Using Follow-up Likelihood as Reward Signal.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Detecting AI Flaws: Target-Driven Attacks on Internal Faults in Language Models.
CoRR, 2024

Mamba Hawkes Process.
CoRR, 2024

HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale.
CoRR, 2024

LLMs for Doctors: Leveraging Medical LLMs to Assist Doctors, Not Replace Them.
CoRR, 2024

LLMs Could Autonomously Learn Without External Supervision.
CoRR, 2024

Unsupervised Mutual Learning of Dialogue Discourse Parsing and Topic Segmentation.
CoRR, 2024

Mamo: a Mathematical Modeling Benchmark with Solvers.
CoRR, 2024

RoTHP: Rotary Position Embedding-based Transformer Hawkes Process.
CoRR, 2024

Apollo: An Lightweight Multilingual Medical LLM towards Democratizing Medical AI to 6B People.
CoRR, 2024

OVM, Outcome-supervised Value Models for Planning in Mathematical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
MLLM-Bench, Evaluating Multi-modal LLMs using GPT-4V.
CoRR, 2023

HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs.
CoRR, 2023

Outcome-supervised Verifiers for Planning in Mathematical Reasoning.
CoRR, 2023


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