1 citations · 2 across the 4 of their papers we have counts for
6 papers
IdeaLens: Detecting AI Ideas in Long-form Writing
Rishanth Rajendhran, Minjoon Choi, Jenna Russell +5
While modern AI detectors identify who wrote the words, emerging policies on AI use increasingly hinge on a different question: who came up with the ideas? We introduce IdeaLens, a…
How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text
Jenna Russell, Ben Glickenhaus, Katherine Thai +4
Web text makes up the majority of pretraining data and is increasingly AI-generated. After applying FineWeb quality filtering, we find that 27.5% of tokens from June 2026 web data…
POLARIS: Guiding Small Models to Write Long Stories
Rishanth Rajendhran, Jenna Russell, Mohit Iyyer +1
Small open-weight models struggle at long-form creative writing: their generated stories either fall far short of the requested length, or their quality significantly degrades as l…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval
Nandan Thakur, Jianmo Ni, Gustavo Hernández Ábrego +3
There has been limited success for dense retrieval models in multilingual retrieval, due to uneven and scarce training data available across multiple languages. Synthetic training…
Evaluating Large Language Models on Controlled Generation Tasks
Jiao Sun, Yufei Tian, Wangchunshu Zhou +6
While recent studies have looked into the abilities of large language models in various benchmark tasks, including question generation, reading comprehension, multilingual and etc,…