activity
20232026
most citedKnowledge Editing for Large Language Models: A Survey

5 citations · 8 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

TeacherGRPO: Closing the Capacity Gap in Reasoning Distillation via Teacher Alignment

Zhenyu Lei, Zihan Chen, Yaochen Zhu +5

Reasoning distillation from powerful teacher models to smaller students faces the Gap Curse: as teachers grow more sophisticated, their complex distributions increasingly diverge f…

cs.AI2026

SAPO: Step-Aligned Policy Optimization for Reasoning-Based Generative Recommendation

Zaiyi Zheng, Liang Wu, Guanghui Min +4

Generative recommendation treats next-item prediction as autoregressive item-identifier generation. Specifically, items are encoded as semantic identifiers (SIDs), which are short…

cs.CL2025

SemCoT: Accelerating Chain-of-Thought Reasoning through Semantically-Aligned Implicit Tokens

Yinhan He, Wendy Zheng, Yaochen Zhu +6

The verbosity of Chain-of-Thought (CoT) reasoning hinders its mass deployment in efficiency-critical applications. Recently, implicit CoT approaches have emerged, which encode reas…

cs.LG2025

Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion

Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen +1

Symmetry in the parameter space of deep neural networks (DNNs) has proven beneficial for various deep learning applications. A well-known example is the permutation symmetry in Mul…

cs.CL2025

Resolving Editing-Unlearning Conflicts: A Knowledge Codebook Framework for Large Language Model Updating

Binchi Zhang, Zhengzhang Chen, Zaiyi Zheng +2

Large Language Models (LLMs) excel in natural language processing by encoding extensive human knowledge, but their utility relies on timely updates as knowledge evolves. Updating L…

cs.AI2025

KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models

Zaiyi Zheng, Yushun Dong, Song Wang +3

Large Language Models (LLMs) have shown impressive performance in various tasks, including knowledge graph completion (KGC). However, current studies mostly apply LLMs to classific…

cs.LG2024

Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction

Yinhan He, Zaiyi Zheng, Patrick Soga +3

In recent years, Graph Neural Networks (GNNs) have become successful in molecular property prediction tasks such as toxicity analysis. However, due to the black-box nature of GNNs,…

cs.LG2024★ 1 cited

A Benchmark for Fairness-Aware Graph Learning

Yushun Dong, Song Wang, Zhenyu Lei +4

Fairness-aware graph learning has gained increasing attention in recent years. Nevertheless, there lacks a comprehensive benchmark to evaluate and compare different fairness-aware…

cs.CL2024★ 2 cited

AI-native Memory: A Pathway from LLMs Towards AGI

Jingbo Shang, Zai Zheng, Jiale Wei +3

Large language models (LLMs) have demonstrated the world with the sparks of artificial general intelligence (AGI). One opinion, especially from some startups working on LLMs, argue…

cs.CL2023★ 5 cited

Knowledge Editing for Large Language Models: A Survey

Song Wang, Yaochen Zhu, Haochen Liu +3

Large language models (LLMs) have recently transformed both the academic and industrial landscapes due to their remarkable capacity to understand, analyze, and generate texts based…