activity
20242026
most citedHidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection

2 citations · 7 across the 11 of their papers we have counts for

collaborators
Showing cs.CLShow all

7 papers · 1 filter

cs.CL2026

Beyond Polarization: The Generative Constraint of Chain-of-Thought in Pointwise Reranking

Xiaoyang Chen, Jie Liu, Haijin Liang +5

In pointwise document reranking, Chain-of-Thought models typically underperform direct scoring models. While existing diagnostics attribute this to inferior classification, score p…

cs.CL2026

Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces

Jiawei Chen, Ruoxi Xu, Boxi Cao +12

The emergence of Large Language Models (LLMs) has illuminated the potential for a general-purpose user simulator. However, existing benchmarks remain constrained to isolated scenar…

cs.CL2025

Memorizing is Not Enough: Deep Knowledge Injection Through Reasoning

Ruoxi Xu, Yunjie Ji, Boxi Cao +7

Although large language models (LLMs) excel in knowledge recall and reasoning, their static nature leads to outdated information as the real world evolves or when adapting to domai…

cs.CL2025★ 1 cited

Large Language Models Often Say One Thing and Do Another

Ruoxi Xu, Hongyu Lin, Xianpei Han +4

As large language models (LLMs) increasingly become central to various applications and interact with diverse user populations, ensuring their reliable and consistent performance i…

cs.CL2024★ 1 cited

Academically intelligent LLMs are not necessarily socially intelligent

Ruoxi Xu, Hongyu Lin, Xianpei Han +2

The academic intelligence of large language models (LLMs) has made remarkable progress in recent times, but their social intelligence performance remains unclear. Inspired by estab…

cs.CL2024★ 2 cited

Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection

Xinlin Peng, Ying Zhou, Ben He +2

Large language models (LLMs) have exhibited remarkable capabilities in text generation tasks. However, the utilization of these models carries inherent risks, including but not lim…

cs.CL2024★ 2 cited

AI for social science and social science of AI: A Survey

Ruoxi Xu, Yingfei Sun, Mengjie Ren +5

Recent advancements in artificial intelligence, particularly with the emergence of large language models (LLMs), have sparked a rethinking of artificial general intelligence possib…