activity
20242026
most citedLogic Rules as Explanations for Legal Case Retrieval

2 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2026

The DAWN of World-Action Interactive Models

Hongbo Lu, Liang Yao, Chenghao He +6

A plausible scene evolution depends on the maneuver being considered, while a good maneuver depends on how the scene may evolve. Existing World Action Models (WAMs) largely miss th…

cs.CL2026

Towards Understanding Continual Factual Knowledge Acquisition of Language Models: From Theory to Algorithm

Haoyu Wang, Yifan Shang, Zhongxiang Sun +3

Continual Pre-Training (CPT) is essential for enabling Language Models (LMs) to integrate new knowledge without erasing old. While classical CPT techniques like data replay have be…

eess.AS2026

Evaluating the Expressive Appropriateness of Speech in Rich Contexts

Tianrui Wang, Ziyang Ma, Yizhou Peng +26

Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its con…

cs.AI2025

Detection and Mitigation of Hallucination in Large Reasoning Models: A Mechanistic Perspective

Zhongxiang Sun, Qipeng Wang, Haoyu Wang +2

Large Reasoning Models (LRMs) have shown impressive capabilities in multi-step reasoning tasks. However, alongside these successes, a more deceptive form of model error has emerged…

cs.CL2024

Effective In-Context Example Selection through Data Compression

Zhongxiang Sun, Kepu Zhang, Haoyu Wang +2

In-context learning has been extensively validated in large language models. However, the mechanism and selection strategy for in-context example selection, which is a crucial ingr…

cs.IR20242 cited

Logic Rules as Explanations for Legal Case Retrieval

Zhongxiang Sun, Kepu Zhang, Weijie Yu +2

In this paper, we address the issue of using logic rules to explain the results from legal case retrieval. The task is critical to legal case retrieval because the users (e.g., law…