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Saranya Venkatraman

7 accepted papers

2025

Beemo: Benchmark of Expert-edited Machine-generated Outputs

NAACL 2025long

The rapid proliferation of large language models (LLMs) has increased the volume of machine-generated texts (MGTs) and blurred text authorship in various domains. However, most existing MGT benchmarks include single-author texts (human-written and machine-generated). This conventional design fails t…

2025

Beyond Checkmate: Exploring the Creative Choke Points for AI Generated Texts

EMNLP 2025

The rapid advancement of Large Language Models (LLMs) has revolutionized text generation but also raised concerns about potential misuse, making detecting LLM-generated text (AI text) increasingly essential. While prior work has focused on identifying AI text and effectively checkmating it, our stud

2025

CollabStory: Multi-LLM Collaborative Story Generation and Authorship Analysis

NAACL 2025findings

The rise of unifying frameworks that enable seamless interoperability of Large Language Models (LLMs) has made LLM-LLM collaboration for open-ended tasks a possibility. Despite this, there have not been efforts to explore such collaborative writing. We take the next step beyond human-LLM collaborati…

2024

A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts

ACL 2024long

In the realm of text manipulation and linguistic transformation, the question of authorship has been a subject of fascination and philosophical inquiry. Much like the Ship of Theseus paradox, which ponders whether a ship remains the same when each of its original planks is replaced, our research del…

2024

ALISON: Fast and Effective Stylometric Authorship Obfuscation

AAAI 2024technical

Authorship Attribution (AA) and Authorship Obfuscation (AO) are two competing tasks of increasing importance in privacy research. Modern AA leverages an author's consistent writing style to match a text to its author using an AA classifier. AO is the corresponding adversarial task, aiming to modify…

2024

GPT-who: An Information Density-based Machine-Generated Text Detector

NAACL 2024findings

The Uniform Information Density (UID) principle posits that humans prefer to spread information evenly during language production. We examine if this UID principle can help capture differences between Large Language Models (LLMs)-generated and human-generated texts. We propose GPT-who, the first psy…

2023

The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis

EMNLP 2023long main

We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our investigation stems from the recognition that SA has become an integral component of diverse sociotechnical systems, exer…

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