activity
20202026
most citedDialect-robust Evaluation of Generated Text

2 citations · 5 across the 12 of their papers we have counts for

collaborators
Showing cs.CLShow all

13 papers · 1 filter

cs.CL2026

Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting

Defu Cao, Zijie Lei, Muyan Weng +2

Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet their discrete, language-oriente…

cs.CL20261 cited

How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks

Longju Bai, Zhemin Huang, Xingyao Wang +5

The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that require a significant amount of t…

cs.CL2025

SWE-IF: Aligning Code Evaluation with Human Preference

Ming Zhong, Xiang Zhou, Ting-Yun Chang +9

Large Language Models (LLMs) have catalyzed vibe coding, where users leverage LLMs to generate and iteratively refine code through natural language interactions until it passes the…

cs.CL2025

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network

Xin Liu, Rongwu Xu, Xinyi Jia +4

The rise of large language models (LLMs) has enabled the generation of highly persuasive spam reviews that closely mimic human writing. These reviews pose significant challenges fo…

cs.CL2025

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

Congmin Zheng, Jiachen Zhu, Jianghao Lin +6

Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially for mathematical problem solving. Howeve…

cs.CL2025

SkillVerse : Assessing and Enhancing LLMs with Tree Evaluation

Yufei Tian, Jiao Sun, Nanyun Peng +1

As language models evolve to tackle complex, multifaceted tasks, their evaluation must adapt to capture this intricacy. A granular, skill-specific understanding of model capabiliti…