Anningzhe Gao
13 papers · 2024–2025 · 4 conferences · across top CS/AI conferences
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NAACL (5)
EMNLP (4)
ACL (3)
AAAI (1)
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Research topics
Keywords
large language model
(6)
reinforcement learning
(3)
domain adaptation
(2)
preference learning
(2)
multimodal large language model
(2)
benchmark evaluation
(2)
reward modeling
(1)
direct preference optimization
(1)
adversarial robustness
(1)
optimal transport
(1)
incremental learning
(1)
visual question answering
(1)
self-supervised learning
(1)
medical imaging
(1)
prompt engineering
(1)
in-context learning
(1)
knowledge distillation
(1)
multimodal learning
(1)
transfer learning
(1)
zero-shot learning
(1)
Papers
Huatuo-26M, a Large-scale Chinese Medical QA Dataset
NAACL 2025
Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
ACL 2025
CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis
ACL 2025
Unlocking LLMsβ Self-Improvement Capacity with Autonomous Learning for Domain Adaptation
ACL 2025
Atoxia: Red-teaming Large Language Models with Target Toxic Answers
NAACL 2025
Aligning Language Models Using Follow-up Likelihood as Reward Signal
AAAI 2025
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
EMNLP 2025
APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport
EMNLP 2025
DRBO: Mitigating the Bottleneck Effect via Dynamic Reward Balancing in Multi-reward LLM Optimization
EMNLP 2025
MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria
NAACL 2025
LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural and Mathematical Languages
NAACL 2025
Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale
EMNLP 2024
OVM, Outcome-supervised Value Models for Planning in Mathematical Reasoning
NAACL 2024