2 citations · 3 across the 10 of their papers we have counts for
12 papers
Recognizing Is Not Reversing: A Controlled Inversion Test of Fact-Preserving News Framing
Yi Liu
Large language models (LLMs) are increasingly used to analyze and rewrite news, yet current framing studies mainly evaluate generation, detection, or whether rewritten text appears…
MAVEN: A Macro-Societal Value Evaluation Framework of Multimodal Content with Compact Aligned Evaluators
Zijuan Zhao, Zheren Fu, Hou Xia +3
Assessing whether multimodal content aligns with macro-societal values, such as peace, justice, and freedom, has become an increasingly urgent challenge. Existing frameworks are la…
FineRef: Fine-Grained Error Reflection and Correction for Long-Form Generation with Citations
Yixing Peng, Licheng Zhang, Shancheng Fang +3
Generating with citations is crucial for trustworthy Large Language Models (LLMs), yet even advanced LLMs often produce mismatched or irrelevant citations. Existing methods over-op…
Mitigating Biases in Language Models via Bias Unlearning
Dianqing Liu, Yi Liu, Guoqing Jin +1
Many studies have shown various biases targeting different demographic groups in language models, amplifying discrimination and harming fairness. Recent parameter modification debi…
Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models
Yi Liu, Dianqing Liu, Mingye Zhu +3
The widespread adoption of large language models (LLMs) across industries has increased the demand for high-quality and customizable outputs. However, traditional alignment methods…
Leveraging Robust Optimization for LLM Alignment under Distribution Shifts
Mingye Zhu, Yi Liu, Zheren Fu +2
Preference alignment methods are increasingly critical for steering large language models (LLMs) to generate outputs consistent with human values. While recent approaches often rel…
On-the-fly Preference Alignment via Principle-Guided Decoding
Mingye Zhu, Yi Liu, Lei Zhang +2
With the rapidly expanding landscape of large language models, aligning model generations with human values and preferences is becoming increasingly important. Popular alignment me…
FlipGuard: Defending Preference Alignment against Update Regression with Constrained Optimization
Mingye Zhu, Yi Liu, Quan Wang +2
Recent breakthroughs in preference alignment have significantly improved Large Language Models' ability to generate texts that align with human preferences and values. However, cur…
LIRE: listwise reward enhancement for preference alignment
Mingye Zhu, Yi Liu, Lei Zhang +2
Recently, tremendous strides have been made to align the generation of Large Language Models (LLMs) with human values to mitigate toxic or unhelpful content. Leveraging Reinforceme…
Gradual Residuals Alignment: A Dual-Stream Framework for GAN Inversion and Image Attribute Editing
Hao Li, Mengqi Huang, Lei Zhang +3
GAN-based image attribute editing firstly leverages GAN Inversion to project real images into the latent space of GAN and then manipulates corresponding latent codes. Recent invers…
Benchmarking Large Language Models on Controllable Generation under Diversified Instructions
Yihan Chen, Benfeng Xu, Quan Wang +2
While large language models (LLMs) have exhibited impressive instruction-following capabilities, it is still unclear whether and to what extent they can respond to explicit constra…
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representation
Jiaang Li, Quan Wang, Yi Liu +2
Representation Learning on Knowledge Graphs (KGs) is essential for downstream tasks. The dominant approach, KG Embedding (KGE), represents entities with independent vectors and fac…