activity
20212026
most citedTopicGPT: A Prompt-based Topic Modeling Framework

12 citations · 24 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CL2026

Argument Collapse: LLMs Flatten Long-Form Public Debate

Yekyung Kim, Yapei Chang, Chau Minh Pham +1

As LLMs are increasingly used to draft publicfacing arguments, they may flatten public debate by repeatedly introducing the same polished, plausible arguments. We study argument co…

cs.CL2026

StoryScope: Investigating idiosyncrasies in AI fiction

Jenna Russell, Rishanth Rajendhran, Chau Minh Pham +2

As AI-generated fiction becomes increasingly prevalent, questions of authorship and originality are becoming central to how written work is evaluated. While most existing work in t…

cs.CL2025

OWL: Probing Cross-Lingual Recall of Memorized Texts via World Literature

Alisha Srivastava, Emir Korukluoglu, Minh Nhat Le +4

Large language models (LLMs) are known to memorize and recall English text from their pretraining data. However, the extent to which this ability generalizes to non-English languag…

cs.CL2025

Frankentext: Stitching random text fragments into long-form narratives

Chau Minh Pham, Jenna Russell, Dzung Pham +1

We introduce Frankentexts, a long-form narrative generation paradigm that treats an LLM as a composer of existing texts rather than as an author. Given a writing prompt and thousan…

cs.CR2025

Can Large Language Models Really Recognize Your Name?

Dzung Pham, Peter Kairouz, Niloofar Mireshghallah +3

Large language models (LLMs) are increasingly being used in privacy pipelines to detect and remedy sensitive data leakage. These solutions often rely on the premise that LLMs can r…

cs.AI2025

BEARCUBS: A benchmark for computer-using web agents

Yixiao Song, Katherine Thai, Chau Minh Pham +3

Modern web agents possess computer use abilities that allow them to interact with webpages by sending commands to a virtual keyboard and mouse. While such agents have considerable…

cs.CL2025

CLIPPER: Compression enables long-context synthetic data generation

Chau Minh Pham, Yapei Chang, Mohit Iyyer

LLM developers are increasingly reliant on synthetic data, but generating high-quality data for complex long-context reasoning tasks remains challenging. We introduce CLIPPER, a co…

cs.CL2025

Whose story is it? Personalizing story generation by inferring author styles

Nischal Ashok Kumar, Chau Minh Pham, Mohit Iyyer +1

Personalization is critical for improving user experience in interactive writing and educational applications, yet remains understudied in story generation. We study the task of pe…

cs.CR2024★ 1 cited

ProxyGPT: Enabling User Anonymity in LLM Chatbots via (Un)Trustworthy Volunteer Proxies

Dzung Pham, Jade Sheffey, Chau Minh Pham +1

Popular large language model (LLM) chatbots such as ChatGPT and Claude require users to create an account with an email or a phone number before allowing full access to their servi…

cs.CL2024

Interactive Topic Models with Optimal Transport

Garima Dhanania, Sheshera Mysore, Chau Minh Pham +3

Topic models are widely used to analyze document collections. While they are valuable for discovering latent topics in a corpus when analysts are unfamiliar with the corpus, analys…

cs.CL2024

Suri: Multi-constraint Instruction Following for Long-form Text Generation

Chau Minh Pham, Simeng Sun, Mohit Iyyer

Existing research on instruction following largely focuses on tasks with simple instructions and short responses. In this work, we explore multi-constraint instruction following fo…

cs.CL2023★ 12 cited

TopicGPT: A Prompt-based Topic Modeling Framework

Chau Minh Pham, Alexander Hoyle, Simeng Sun +2

Topic modeling is a well-established technique for exploring text corpora. Conventional topic models (e.g., LDA) represent topics as bags of words that often require "reading the t…

cs.HC2023★ 11 cited

AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms

Zana Buçinca, Chau Minh Pham, Maurice Jakesch +3

While demands for change and accountability for harmful AI consequences mount, foreseeing the downstream effects of deploying AI systems remains a challenging task. We developed AH…

cs.CL2021

Emotion analysis and detection during COVID-19

Tiberiu Sosea, Chau Pham, Alexander Tekle +2

Crises such as natural disasters, global pandemics, and social unrest continuously threaten our world and emotionally affect millions of people worldwide in distinct ways. Understa…