activity
20212026
most citedEvaluating and Inducing Personality in Pre-trained Language Models

43 citations · 63 across the 28 of their papers we have counts for

collaborators

28 papers

cs.CL2026

Multi-Level Narrative Evaluation Outperforms Lexical Features for Mental Health

Yuxi Ma, Jieming Cui, Muyang Li +6

How people narrate their experiences offers a window into how the mind organizes them. Computational approaches to therapeutic writing have evolved from lexical counting to neural…

cs.AI2026

Visual Distraction Undermines Moral Reasoning in Vision-Language Models

Xinyi Yang, Chenheng Xu, Weijun Hong +4

Moral reasoning is fundamental to safe Artificial Intelligence (AI), yet ensuring its consistency across modalities becomes critical as AI systems evolve from text-based assistants…

cs.HC2026

NarrativeLoom: Enhancing Creative Storytelling through Multi-Persona Collaborative Improvisation

Yuxi Ma, Yongqian Peng, Fengyuan Yang +5

Large Language Models show promise for AI-assisted storytelling, yet current tools often generate predictable, unoriginal narratives. To address this limitation, we present Narrati…

cs.CV2026★ 1 cited

Learning Physics-Grounded 4D Dynamics with Neural Gaussian Force Fields

Shiqian Li, Ruihong Shen, Junfeng Ni +3

Predicting physical dynamics from raw visual data remains a major challenge in AI. While recent video generation models have achieved impressive visual quality, they still cannot c…

cs.CL2026

Code over Words: Overcoming Semantic Inertia via Code-Grounded Reasoning

Manjie Xu, Isabella Yin, Xinyi Tu +2

LLMs struggle with Semantic Inertia: the inability to inhibit pre-trained priors (e.g., "Lava is Dangerous") when dynamic, in-context rules contradict them. We probe this phenomeno…

cs.AI2026

BotzoneBench: Scalable LLM Evaluation via Graded AI Anchors

Lingfeng Li, Yunlong Lu, Yuefei Zhang +7

Large Language Models (LLMs) are increasingly deployed in interactive environments requiring strategic decision-making, yet systematic evaluation of these capabilities remains chal…

cs.IR2025

Cross-Scenario Unified Modeling of User Interests at Billion Scale

Manjie Xu, Cheng Chen, Xin Jia +9

User interests on content platforms are inherently diverse, manifesting through complex behavioral patterns across heterogeneous scenarios such as search, feed browsing, and conten…

physics.ed-ph2025

A simulation-heuristics dual-process model for intuitive physics

Shiqian Li, Yuxi Ma, Jiajun Yan +4

The role of mental simulation in human physical reasoning is widely acknowledged, but whether it is employed across scenarios with varying simulation costs and where its boundary l…

cs.CV2025

Probing and Inducing Combinational Creativity in Vision-Language Models

Yongqian Peng, Yuxi Ma, Mengmeng Wang +5

The ability to combine existing concepts into novel ideas stands as a fundamental hallmark of human intelligence. Recent advances in Vision-Language Models (VLMs) like GPT-4V and D…

cs.CL2025

Word Embeddings Track Social Group Changes Across 70 Years in China

Yuxi Ma, Yongqian Peng, Yixin Zhu

Language encodes societal beliefs about social groups through word patterns. While computational methods like word embeddings enable quantitative analysis of these patterns, studie…

cs.LG2025

Neural Force Field: Few-shot Learning of Generalized Physical Reasoning

Shiqian Li, Ruihong Shen, Yaoyu Tao +2

Physical reasoning is a remarkable human ability that enables rapid learning and generalization from limited experience. Current AI models, despite extensive training, still strugg…

cs.AI2025

Inferring the Unspoken: Aligning Embodied Agents with Implicit Preferences

Manjie Xu, Xinyi Yang, Wei Liang +2

Natural-language instructions rarely specify every detail required for embodied action. An agent asked to ``prepare an apple,'' for example, must still determine whether to wash or…

cs.AI2024★ 1 cited

Proposing and solving olympiad geometry with guided tree search

Chi Zhang, Jiajun Song, Siyu Li +5

Mathematics olympiads are prestigious competitions, with problem proposing and solving highly honored. Building artificial intelligence that proposes and solves olympiads presents…

cs.NE2024★ 1 cited

Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning

Mingqing Xiao, Yixin Zhu, Di He +1

Spiking neural networks (SNNs) are investigated as biologically inspired models of neural computation, distinguished by their computational capability and energy efficiency due to…

cs.AI2024

Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI Capabilities

Junqi Wang, Chunhui Zhang, Jiapeng Li +6

Facing the current debate on whether Large Language Models (LLMs) attain near-human intelligence levels (Mitchell & Krakauer, 2023; Bubeck et al., 2023; Kosinski, 2023; Shiffrin &…

cs.AI2023

I-PHYRE: Interactive Physical Reasoning

Shiqian Li, Kewen Wu, Chi Zhang +1

Current evaluation protocols predominantly assess physical reasoning in stationary scenes, creating a gap in evaluating agents' abilities to interact with dynamic events. While con…

cs.AI2023★ 3 cited

Active Reasoning in an Open-World Environment

Manjie Xu, Guangyuan Jiang, Wei Liang +2

Recent advances in vision-language learning have achieved notable success on complete-information question-answering datasets through the integration of extensive world knowledge.…

cs.AI2023

X-VoE: Measuring eXplanatory Violation of Expectation in Physical Events

Bo Dai, Linge Wang, Baoxiong Jia +4

Intuitive physics is pivotal for human understanding of the physical world, enabling prediction and interpretation of events even in infancy. Nonetheless, replicating this level of…

cs.CL2023★ 5 cited

MEWL: Few-shot multimodal word learning with referential uncertainty

Guangyuan Jiang, Manjie Xu, Shiji Xin +4

Without explicit feedback, humans can rapidly learn the meaning of words. Children can acquire a new word after just a few passive exposures, a process known as fast mapping. This…

cs.AI2022

To think inside the box, or to think out of the box? Scientific discovery via the reciprocation of insights and concepts

Yu-Zhe Shi, Manjie Xu, Wenjuan Han +1

If scientific discovery is one of the main driving forces of human progress, insight is the fuel for the engine, which has long attracted behavior-level research to understand and…

cs.LG2022

On the Learning Mechanisms in Physical Reasoning

Shiqian Li, Kewen Wu, Chi Zhang +1

Is dynamics prediction indispensable for physical reasoning? If so, what kind of roles do the dynamics prediction modules play during the physical reasoning process? Most studies f…

cs.AI2022★ 1 cited

Interactive Visual Reasoning under Uncertainty

Manjie Xu, Guangyuan Jiang, Wei Liang +2

One of the fundamental cognitive abilities of humans is to quickly resolve uncertainty by generating hypotheses and testing them via active trials. Encountering a novel phenomenon…

cs.CL2022★ 43 cited

Evaluating and Inducing Personality in Pre-trained Language Models

Guangyuan Jiang, Manjie Xu, Song-Chun Zhu +3

Standardized and quantified evaluation of machine behaviors is a crux of understanding LLMs. In this study, we draw inspiration from psychometric studies by leveraging human person…

cs.AI2021★ 1 cited

Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning

Chi Zhang, Sirui Xie, Baoxiong Jia +3

Is intelligence realized by connectionist or classicist? While connectionist approaches have achieved superhuman performance, there has been growing evidence that such task-specifi…