4 citations · 5 across the 10 of their papers we have counts for
12 papers
Can We Believe AI Peer Review?
Zongrui Yang, Haoyuan Li, Zhongsheng Wang +2
As large language models become widely used in scientific review and manuscript revision, AI scores are increasingly serving as feedback for assessing paper quality and guiding edi…
SDO: Subspace Deconflicting Operator for Multi-Adapter Composition
Zhongsheng Wang, Zhedong Lin, Qian Liu +2
Composing independently trained adapters within a shared diffusion backbone provides a modular approach to multi-character generation, but naive joint deployment often causes ident…
Creative Convergence or Imitation? Genre-Specific Homogeneity in LLM-Generated Chinese Literature
Yuanchi Ma, Kaize Shi, Hui He +5
Large Language Models (LLMs) have demonstrated remarkable capabilities in narrative generation. However, they often produce structurally homogenized stories, frequently following r…
CharCom: Composable Identity Control for Multi-Character Story Illustration
Zhongsheng Wang, Ming Lin, Zhedong Lin +3
Ensuring character identity consistency across varying prompts remains a fundamental limitation in diffusion-based text-to-image generation. We propose CharCom, a modular and param…
Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm
Yang Chen, Menglin Zou, Jiaqi Zhang +6
Inverse Reinforcement Learning (IRL) learns a reward function to explain expert demonstrations. Modern IRL methods often use the adversarial (minimax) formulation that alternates b…
Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables
Yang Chen, Xiao Lin, Bo Yan +4
Designing suitable reward functions for numerous interacting intelligent agents is challenging in real-world applications. Inverse reinforcement learning (IRL) in mean field games…
Weak Supervision Techniques towards Enhanced ASR Models in Industry-level CRM Systems
Zhongsheng Wang, Sijie Wang, Jia Wang +3
In the design of customer relationship management (CRM) systems, accurately identifying customer types and offering personalized services are key to enhancing customer satisfaction…
Situational-Constrained Sequential Resources Allocation via Reinforcement Learning
Libo Zhang, Yang Chen, Toru Takisaka +3
Sequential Resource Allocation with situational constraints presents a significant challenge in real-world applications, where resource demands and priorities are context-dependent…
CoRA: Optimizing Low-Rank Adaptation with Common Subspace of Large Language Models
Xiaojun Xiao, Sen Shen, Qiming Bao +4
In fine-tuning large language models (LLMs), conserving computational resources while maintaining effectiveness and improving outcomes within the same computational constraints is…
ChatLogic: Integrating Logic Programming with Large Language Models for Multi-Step Reasoning
Zhongsheng Wang, Jiamou Liu, Qiming Bao +2
Large language models (LLMs) such as ChatGPT and GPT-4 have demonstrated impressive capabilities in various generative tasks. However, their performance is often hampered by limita…
Behaviour Modelling of Social Animals via Causal Structure Discovery and Graph Neural Networks
Gaël Gendron, Yang Chen, Mitchell Rogers +11
Better understanding the natural world is a crucial task with a wide range of applications. In environments with close proximity between humans and animals, such as zoos, it is ess…
Assessing and Enhancing the Robustness of Large Language Models with Task Structure Variations for Logical Reasoning
Qiming Bao, Gael Gendron, Alex Yuxuan Peng +5
Large language models (LLMs), such as LLaMA, Alpaca, Vicuna, GPT-3.5 and GPT-4, have advanced the performance of AI systems on various natural language processing tasks to human-li…