I'm excited to share our preprint answering these questions:
"Epistemic Diversity and Knowledge Collapse in Large Language Models"
📄Paper: arxiv.org/pdf/2510.04226
💻Code: github.com/dwright37/ll...
1/10
📍 Here's where to find us ⤵️
@apepa.bsky.social @rnv.bsky.social @dustinbwright.com @zainmujahid.me @gretawarren.bsky.social @lovhag.bsky.social @saravera.bsky.social @iaugenstein.bsky.social
#NLProc #AI
📍 Here's where to find us ⤵️
@apepa.bsky.social @rnv.bsky.social @dustinbwright.com @zainmujahid.me @gretawarren.bsky.social @lovhag.bsky.social @saravera.bsky.social @iaugenstein.bsky.social
#NLProc #AI
The talk explored how diverse are the information and perspectives that people are being exposed to in this new era.
#NLProc
The talk explored how diverse are the information and perspectives that people are being exposed to in this new era.
#NLProc
It beats every model, even though it is underestimated.
In other words, one can expect less information from an LLM vs Google searching.
See the new results here! arxiv.org/pdf/2510.04226
It beats every model, even though it is underestimated.
In other words, one can expect less information from an LLM vs Google searching.
See the new results here! arxiv.org/pdf/2510.04226
💻 The code is now a python package! Installation instructions here: github.com/dwright37/ll...
🤗 All 1.6M model responses and 70M clustered claims are now available on HuggingFace! huggingface.co/datasets/dwr...
📄 Paper: arxiv.org/pdf/2510.04226
💻 The code is now a python package! Installation instructions here: github.com/dwright37/ll...
🤗 All 1.6M model responses and 70M clustered claims are now available on HuggingFace! huggingface.co/datasets/dwr...
📄 Paper: arxiv.org/pdf/2510.04226
www.copenlu.com/news/8-paper...
@apepa.bsky.social @rnv.bsky.social @kirekara.bsky.social @shoejoe.bsky.social @dustinbwright.com @zainmujahid.me @lucasresck.bsky.social @iaugenstein.bsky.social
#NLProc #AI #EMNLP2025
www.copenlu.com/news/8-paper...
@apepa.bsky.social @rnv.bsky.social @kirekara.bsky.social @shoejoe.bsky.social @dustinbwright.com @zainmujahid.me @lucasresck.bsky.social @iaugenstein.bsky.social
#NLProc #AI #EMNLP2025
⏰ When: Fri. Nov 7 14:00-15:30
🗺️ Where: Hall C
I'm unable to attend but @iaugenstein.bsky.social will present our work!
⏰ When: Fri. Nov 7 14:00-15:30
🗺️ Where: Hall C
I'm unable to attend but @iaugenstein.bsky.social will present our work!
I'm excited to share our preprint answering these questions:
"Epistemic Diversity and Knowledge Collapse in Large Language Models"
📄Paper: arxiv.org/pdf/2510.04226
💻Code: github.com/dwright37/ll...
1/10
I'm excited to share our preprint answering these questions:
"Epistemic Diversity and Knowledge Collapse in Large Language Models"
📄Paper: arxiv.org/pdf/2510.04226
💻Code: github.com/dwright37/ll...
1/10
"Unstructured Evidence Attribution for Long Context Query Focused Summarization"
w/ @zainmujahid.me , Lu Wang, @iaugenstein.bsky.social , and @davidjurgens.bsky.social
"Unstructured Evidence Attribution for Long Context Query Focused Summarization"
w/ @zainmujahid.me , Lu Wang, @iaugenstein.bsky.social , and @davidjurgens.bsky.social
You can read “Efficiency is Not Enough: A Critical Perspective on Environmentally Sustainable AI” now in CACM!!!
dl.acm.org/doi/10.1145/...
You can read “Efficiency is Not Enough: A Critical Perspective on Environmentally Sustainable AI” now in CACM!!!
dl.acm.org/doi/10.1145/...
@dustinbwright.com @ic2s2.bsky.social #ic2s2
@dustinbwright.com @ic2s2.bsky.social #ic2s2
See the preprint of this work here: arxiv.org/abs/2409.08330
See the preprint of this work here: arxiv.org/abs/2409.08330
Check out the paper ojs.aaai.org/index.php/IC... and models huggingface.co/ariannap22
Feat. poster and research buddy @alessianetwork.bsky.social ♥️
Check out the paper ojs.aaai.org/index.php/IC... and models huggingface.co/ariannap22
Feat. poster and research buddy @alessianetwork.bsky.social ♥️
If you want to apply to work with me and Johannes Bjerva at @aau.dk Copenhagen, I'll be at @ic2s2.bsky.social this week and @aclmeeting.bsky.social next week! DM me if you'd like to meet :)
If you want to apply to work with me and Johannes Bjerva at @aau.dk Copenhagen, I'll be at @ic2s2.bsky.social this week and @aclmeeting.bsky.social next week! DM me if you'd like to meet :)
cacm.acm.org/sustainabili...
cacm.acm.org/sustainabili...
🇩🇰 With international NLP experts from Columbia, UCLA, University of Michigan, and more to Copenhagen to meet with the Danish NLP community. 🇩🇰
📅 Poster submission deadline: June 16, 2025
🔗 Register: www.aicentre.dk/events/pre-a...
🇩🇰 With international NLP experts from Columbia, UCLA, University of Michigan, and more to Copenhagen to meet with the Danish NLP community. 🇩🇰
📅 Poster submission deadline: June 16, 2025
🔗 Register: www.aicentre.dk/events/pre-a...
We show: fact checking w/ crowd workers is more efficient when using LLM summaries, quality doesn't suffer.
arxiv.org/abs/2501.18265
@aicentre.dk
climateainordics.com/newsletter/2...
@aicentre.dk
huggingface.co/datasets/dwr...
Use it as a training or a test set for long context query focused summarization! It includes evidence attribution of free-form text spans from the context, making summaries more transparent and reliable!
huggingface.co/datasets/dwr...
Use it as a training or a test set for long context query focused summarization! It includes evidence attribution of free-form text spans from the context, making summaries more transparent and reliable!
We propose *unstructured* evidence attribution for long context summarization and a synthetic dataset called SUnsET which can help models perform this task.
Paper link: arxiv.org/abs/2502.14409
Thread ⬇️
We propose *unstructured* evidence attribution for long context summarization and a synthetic dataset called SUnsET which can help models perform this task.
Paper link: arxiv.org/abs/2502.14409
Thread ⬇️
We show: fact checking w/ crowd workers is more efficient when using LLM summaries, quality doesn't suffer.
arxiv.org/abs/2501.18265
We show: fact checking w/ crowd workers is more efficient when using LLM summaries, quality doesn't suffer.
arxiv.org/abs/2501.18265