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[3/4] Do VLMs actually ground in the figure? Fine-tuning Qwen3.5-9B on MQUD makes generated questions more grounded in the figure and more specific to the paper’s scientific content.
1mo
Yating Wu
What does a scientific figure make you wonder? πŸ“Š We introduce MQUD: multimodal Questions Under Discussion for scientific figures. With 1,250 author-annotated questions over 245 figures from 56 papers, MQUD asks what scientific question a figure raises in context.
Nov 22, 2024
1mo
I did a starter pack of ML/AI people at @utaustin.bsky.social Please distribute and feel free to self nominate! go.bsky.app/QLQznZg
at://did:plc:vz2my7lhvw254yf43nom4otr/app.bsky.graph.starterpack/3lbjnpo4jc32a
Yating Wu
Atlas Wang
Do you want to know what information LLMs prioritize in text synthesis tasks? Here's a short 🧡 about our new paper, led by Jan Trienes: an interpretable framework for salience analysis in LLMs. First of all, information salience is a fuzzy concept. So how can we even measure it? (1/6)
Feb 21, 2025
Apr 21, 2025
Check out our paper for more results and analysis! πŸ“ arxiv.org/abs/2504.09373 πŸ™ github.com/AlliteraryAl... This was a fun collaboration with @yatingwu.bsky.social @asher-zheng.bsky.social @manyawadhwa.bsky.social @gregdnlp.bsky.social @jessyjli.bsky.social
As large language models become increasingly capable at various writing tasks, their weakness at generating unique and creative content becomes a major liability. Although LLMs have the ability to gen...
arxiv.org
QUDsim: Quantifying Discourse Similarities in LLM-Generated Text
[4/4] Paper: arxiv.org/abs/2604.23733 Project page: lingchensanwen.github.io/multimodal-q... Dataset: huggingface.co/datasets/lin... w/ William Rudman, @venkatasg.net @alexdimakis.bsky.social, @jessyjli.bsky.social
1mo