1 citations · 1 across the 10 of their papers we have counts for
10 papers
Beyond Sufficiency: Time Series Explanation with Counterfactual Necessity
Hongnan Ma, Yiwei Shi, Mengyue Yang +1
Faithful explanations of time-series classifiers should identify subsequences that are not only sufficient to preserve a black-box model's prediction, but also necessary for mainta…
Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields
Yiwei Shi, Zixing Song, Mengyue Yang +2
{Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer latent field parameters under st…
CreativeGame:Toward Mechanic-Aware Creative Game Generation
Hongnan Ma, Han Wang, Shenglin Wang +6
Large language models can generate plausible game code, but turning this capability into \emph{iterative creative improvement} remains difficult. In practice, single-shot generatio…
Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference
David Fox, Sam Bowyer, Song Liu +3
Masked discrete diffusion models (MDMs) are a promising new approach to generative modelling, offering the ability for parallel token generation and therefore greater efficiency th…
Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration
Yiwei Shi, Hongnan Ma, Mengyue Yang +2
In emergency response and other high-stakes societal applications, early-stage state estimates critically shape downstream outcomes. Yet, these initial state estimates-often based…
TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation
Hongnan Ma, Yiwei Shi, Guanxiong Sun +2
In decision-making processes, stakeholders often rely on counterfactual explanations, which provide suggestions about what should be changed in the queried instance to alter the ou…
A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
Congmin Zheng, Jiachen Zhu, Zhuoying Ou +8
Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward models (ORMs) that judge only final ans…
Fine-Grained Interpretation of Political Opinions in Large Language Models
Jingyu Hu, Mengyue Yang, Mengnan Du +1
Studies of LLMs' political opinions mainly rely on evaluations of their open-ended responses. Recent work indicates that there is a misalignment between LLMs' responses and their i…
Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering
Yiwei Shi, Jingyu Hu, Yu Zhang +4
Particle filtering is a Bayesian inference method and a fundamental tool in state estimation for dynamic systems, but its effectiveness is often limited by the constraints of the i…
Belief-Contraction-Driven Active Inverse Source Localization and Characterization
Yiwei Shi, Mengyue Yang, Qi Zhang +3
Active inverse source localization and characterization (ISLC) in dynamic fields requires sequential decision making under partial observability, where a mobile sensor must infer l…