papers

Publications (7)

cs.CL2024

Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection Framework

Zhen Tao, Zhiyu Li, Runyu Chen +2

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises conce…

cs.CL2026

Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL

Yihan Wang, Peiyu Liu, Runyu Chen +1

Text-to-SQL has recently achieved impressive progress, yet remains difficult to apply effectively in real-world scenarios. This gap stems from the reliance on single static workflo…

cs.CV2025

DynamicVerse: A Physically-Aware Multimodal Framework for 4D World Modeling

Kairun Wen, Yuzhi Huang, Runyu Chen +16

Understanding the dynamic physical world, characterized by its evolving 3D structure, real-world motion, and semantic content with textual descriptions, is crucial for human-agent…

quant-ph2026

Energy Transport in Randomly Coupled Quantum Systems: A Perturbative Approach

Tingfei Li, Runyu Chen

We study energy transport between two quantum systems coupled through a random interaction. The central feature of our approach is to model the coupling as a Gaussian random matrix…

cs.LG2026

CausalTAD: Injecting Causal Knowledge into Large Language Models for Tabular Anomaly Detection

Ruiqi Wang, Ruikang Liu, Runyu Chen +4

Detecting anomalies in tabular data is critical for many real-world applications, such as credit card fraud detection. With the rapid advancements in large language models (LLMs),…

cs.CL2025

Squrve: A Unified and Modular Framework for Complex Real-World Text-to-SQL Tasks

Yihan Wang, Peiyu Liu, Runyu Chen +2

Text-to-SQL technology has evolved rapidly, with diverse academic methods achieving impressive results. However, deploying these techniques in real-world systems remains challengin…

cs.CL2025

LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams

Yongxuan Wu, Runyu Chen, Peiyu Liu +1

Long-context understanding poses significant challenges in natural language processing, particularly for real-world dialogues characterized by speech-based elements, high redundanc…