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20222025
most citedParaphrasing evades detectors of AI-generated text, but retrieval is an effective defense

91 citations · 101 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CL2025★ 1 cited

Does quantization affect models' performance on long-context tasks?

Anmol Mekala, Anirudh Atmakuru, Yixiao Song +2

Large language models (LLMs) now support context windows exceeding 128K tokens, but this comes with significant memory requirements and high inference latency. Quantization can mit…

cs.CL2024

Localizing and Mitigating Errors in Long-form Question Answering

Rachneet Sachdeva, Yixiao Song, Mohit Iyyer +1

Long-form question answering (LFQA) aims to provide thorough and in-depth answers to complex questions, enhancing comprehension. However, such detailed responses are prone to hallu…

cs.CL2024

VERISCORE: Evaluating the factuality of verifiable claims in long-form text generation

Yixiao Song, Yekyung Kim, Mohit Iyyer

Existing metrics for evaluating the factuality of long-form text, such as FACTSCORE (Min et al., 2023) and SAFE (Wei et al., 2024), decompose an input text into "atomic claims" and…

cs.CL2023★ 2 cited

GEE! Grammar Error Explanation with Large Language Models

Yixiao Song, Kalpesh Krishna, Rajesh Bhatt +2

Grammatical error correction tools are effective at correcting grammatical errors in users' input sentences but do not provide users with \textit{natural language} explanations abo…

cs.CL2023★ 4 cited

A Critical Evaluation of Evaluations for Long-form Question Answering

Fangyuan Xu, Yixiao Song, Mohit Iyyer +1

Long-form question answering (LFQA) enables answering a wide range of questions, but its flexibility poses enormous challenges for evaluation. We perform the first targeted study o…

cs.CL2023

KNN-LM Does Not Improve Open-ended Text Generation

Shufan Wang, Yixiao Song, Andrew Drozdov +3

In this paper, we study the generation quality of interpolation-based retrieval-augmented language models (LMs). These methods, best exemplified by the KNN-LM, interpolate the LM's…

cs.CL2023★ 91 cited

Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense

Kalpesh Krishna, Yixiao Song, Marzena Karpinska +2

The rise in malicious usage of large language models, such as fake content creation and academic plagiarism, has motivated the development of approaches that identify AI-generated…

cs.CL2022★ 2 cited

DEMETR: Diagnosing Evaluation Metrics for Translation

Marzena Karpinska, Nishant Raj, Katherine Thai +3

While machine translation evaluation metrics based on string overlap (e.g., BLEU) have their limitations, their computations are transparent: the BLEU score assigned to a particula…

cs.CL2022★ 1 cited

SLING: Sino Linguistic Evaluation of Large Language Models

Yixiao Song, Kalpesh Krishna, Rajesh Bhatt +1

To understand what kinds of linguistic knowledge are encoded by pretrained Chinese language models (LMs), we introduce the benchmark of Sino LINGuistics (SLING), which consists of…