🏆 𝗕𝗲𝘀𝘁 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱 @ 𝗔𝗖𝗟 𝟮𝟬𝟮𝟲 Thrilled to share that our linguistic paper "The Imperfective Paradox in LLMs" received a Best Paper Award at #ACL2026 ! 🎉 Hoping this encourages more linguistics-informed evaluation in NLP. aclanthology.org/2026.acl-lon...
🧠For this week’s lab seminar, @boleima.bsky.social talked about how survey methodology can inform NLP research, from annotations to human–AI alignment. #NLProc
Tomorrow, Wednesday, July 30, from 11:00-12:30 at #ACL2025 I am presenting our poster on surveying resources for understanding pragmatics in NLP models. Feel free to drop by and discuss! 📍Hall 4X, Poster board 374 aclanthology.org/2025.acl-lon...
Bolei Ma@boleima.bsky.social · last yr.🤔 Can LLMs read between the lines? Our another #ACL2025 paper surveys resources on how LLMs handle pragmatics like implicatures, deixis, and more. We map out a new landscape for both LLMs and linguistics in pragmatic research. 📄 arxiv.org/abs/2502.12378 🧠💬 #LLMs #Pragmatics
I am presenting this paper today at 2PM in Room 1.62 (Session 3: IP-Orals). Feel free to attend and reach out if you’d like to discuss ~ #ACL2025
Bolei Ma@boleima.bsky.social · last yr.🎉 Our paper “Algorithmic Fidelity of LLMs in Generating Synthetic German Public Opinions” is accepted at #ACL2025 main conference as an oral presentation! 🇩🇪🤖 We study how well LLMs simulate real survey responses using open-ended German data, showing the left-leaning bias.
Headed to ACL? MaiNLP & our most recent work will be there too👥📄 Come see what we’ve been working on!
🤔 Can LLMs read between the lines? Our another #ACL2025 paper surveys resources on how LLMs handle pragmatics like implicatures, deixis, and more. We map out a new landscape for both LLMs and linguistics in pragmatic research. 📄 arxiv.org/abs/2502.12378 🧠💬 #LLMs #Pragmatics
🎉 Our paper “Algorithmic Fidelity of LLMs in Generating Synthetic German Public Opinions” is accepted at #ACL2025 main conference as an oral presentation! 🇩🇪🤖 We study how well LLMs simulate real survey responses using open-ended German data, showing the left-leaning bias.