activity
20242026
collaborators

6 papers

cs.CL2026

Fast Numbers, Slow Language: Bridging Quantitative and Qualitative Earnings Signals

Ding Yu, Zhuo Liu, Hao Zhang +1

Earnings announcements release two types of information sequentially: quantitative surprise (numeric earnings-per-share (EPS)/revenue versus analyst estimate) arrives first in pres…

cs.CL2026

Style or Content? Evaluating Style Classifiers with Controlled Content Overlap

Zhuo Liu, Haozheng Du, Xiangxiang Xu +1

Style classifiers can use content cues that correlate with style labels in naturally collected data, yet we lack a systematic way to measure this reliance. We study this problem wi…

cs.CL2025

TreeRare: Syntax Tree-Guided Retrieval and Reasoning for Knowledge-Intensive Question Answering

Boyi Zhang, Zhuo Liu, Hangfeng He

In real practice, questions are typically complex and knowledge-intensive, requiring Large Language Models (LLMs) to recognize the multifaceted nature of the question and reason ac…

cs.CL2025

Mitigating Hallucinations in Multimodal Spatial Relations through Constraint-Aware Prompting

Jiarui Wu, Zhuo Liu, Hangfeng He

Spatial relation hallucinations pose a persistent challenge in large vision-language models (LVLMs), leading to generate incorrect predictions about object positions and spatial co…

cs.CL2024

Same Company, Same Signal: The Role of Identity in Earnings Call Transcripts

Ding Yu, Zhuo Liu, Hangfeng He

Post-earnings volatility prediction is critical for investors, with previous works often leveraging earnings call transcripts under the assumption that their rich semantics contrib…

cs.AI2024

On the Role of Model Prior in Real-World Inductive Reasoning

Zhuo Liu, Ding Yu, Hangfeng He

Large Language Models (LLMs) show impressive inductive reasoning capabilities, enabling them to generate hypotheses that could generalize effectively to new instances when guided b…