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Hao Liu — most-cited papers & profile · Large Language Models
← authors
·
overview
Hao Liu
115
papers ·
552
citations ·
19
h-index
Shanghai University · Guangzhou University of Chinese Medicine · New York City Fire Department · Shenyang Institute of Automation · Hebei University of Technology · First Affiliated Hospital of Guangzhou University of Chinese Medicine
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Most-cited papers
TrustLLM: Trustworthiness in Large Language Models
2024 · 53 citations
Adversarial Tuning: Defending Against Jailbreak Attacks For Llms
2024 · 31 citations
Beyond Numeric Rewards: In-context Dueling Bandits With LLM Agents
2024 · 4 citations
Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans
2024 · 3 citations
Towards Better Few-Shot and Finetuning Performance with Forgetful Causal Language Models
2022 · 1 citations
Agent-Omit: Training Efficient LLM Agents for Adaptive Thought and Observation Omission via Agentic Reinforcement Learning
2026
Gradmap: Faster Layer Pruning With Gradient Metric And Projection Compensation
2026
Hard vs. Noise: Resolving Hard-Noisy Sample Confusion in Recommender Systems via Large Language Models
2025
An Efficient LLM-based Evolutional Recommendation with Locate-Forget-Update Paradigm
2025
Multi-Value Alignment for LLMs via Value Decorrelation and Extrapolation
2025
WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
2025
MIST: Towards Multi-dimensional Implicit BiaS Evaluation of LLMs for Theory of Mind
2025
A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
2025
The False Promise of Imitating Proprietary LLMs
2023
ChipNeMo: Domain-Adapted LLMs for Chip Design
2023
Top co-authors
Le Wu
· 3
Pieter Abbeel
· 3
Min Hou
· 2
Sergey Levine
· 2
Si Wei
· 2
Xin Li
· 2
Xinyang Geng
· 2
Aakash Naik
· 1
Abdelrahman Ibrahim
· 1
Abhijeet Sadashiv Gangan
· 1
Adib Bazgir
· 1
Ahmed Ilyas
· 1
Topics
Training Techniques
Fine-Tuning
Efficiency
Evaluation
Model Architecture
Safety & Alignment
Reinforcement Learning
In-Context Learning
Code
Prompting