30 citations · 47 across the 24 of their papers we have counts for
5 papers · 1 filter
DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios
Junchao Wu, Runzhe Zhan, Derek F. Wong +4
Detecting text generated by large language models (LLMs) is of great recent interest. With zero-shot methods like DetectGPT, detection capabilities have reached impressive levels.…
VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning
Jingkun Ma, Runzhe Zhan, Yang Li +4
A hallmark of advanced artificial intelligence is the capacity to progress from passive visual perception to the strategic modification of visual information to facilitate complex…
Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore
Junchao Wu, Runzhe Zhan, Derek F. Wong +4
The efficacy of detectors for texts generated by large language models (LLMs) substantially depends on the availability of large-scale training data. However, white-box zero-shot d…
Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model
Runzhe Zhan, Xinyi Yang, Derek F. Wong +2
While supervised fine-tuning (SFT) has been a straightforward approach for tailoring the output of foundation large language model (LLM) to specific preferences, concerns have been…
Let's Focus on Neuron: Neuron-Level Supervised Fine-tuning for Large Language Model
Haoyun Xu, Runzhe Zhan, Derek F. Wong +1
Large Language Models (LLMs) are composed of neurons that exhibit various behaviors and roles, which become increasingly diversified as models scale. Recent studies have revealed t…