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Reposted by Jing Yang

Jing Yang @jingyng.bsky.social · 28/05/2026

📢 Call for Papers We're organizing the 5th edition of MUWS: Workshop Multimodal Human Understanding for the Web and Social Media @ ACM Multimedia 2026 in Rio de Janeiro, Brazil! 🇧🇷 🗓️ Deadline: July 16, 2026 🔗 Full CFP: muws-workshop.github.io/cfp/ #ACMMM #MUWS 🔗 muws-workshop.github.io/cfp/

muws-workshop.github.io

Call for Papers | MUWS 2026

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Jing Yang @jingyng.bsky.social · 28/05/2026

🚨 Important Dates (AoE): 📝 Submission: July 16, 2026 🔔 Notification: Aug 6, 2026 📷 Camera-Ready: Aug 20, 2026 Submit via OpenReview: openreview.net/group?id=acm... Questions? 📧 muws-workshop@listserv.dfn.de Please share & submit! #ACMMM

openreview.net

ACMMM 2026 Workshop MUWS

Welcome to the OpenReview homepage for ACMMM 2026 Workshop MUWS

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Jing Yang @jingyng.bsky.social · 28/05/2026

Track 2: Understanding Impactful World Events 🌍 Analyze global events using our datasets! Expanded for 2026 with recent events & Portuguese resources to engage with the local Brazilian community. 📊 1.5M+ multilingual tweets 📊 News bias (Left/Right/Center) 🔗 forms.gle/tLJEZfJsnYhW...

forms.gle

MUWS 2026 @ ACM MM - Track 2 Datasets

Please complete the form below to request access to the dataset for this track. Upon submission, a download link along with further instructions to obtain the dataset will be sent to your email addres...

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Jing Yang @jingyng.bsky.social · 28/05/2026

Track 1: Human-Centred Multimodal Understanding 🧠 We seek original papers bridging text & multimedia. Topics include, but not limited to: ✨ Multimodal sentiment & emotion recognition ✨ Bias in Web & Social Media ✨ Semiotics & Gestalt-theory in AI ✨ Hate speech & misinformation detection

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Jing Yang @jingyng.bsky.social · 28/05/2026

muws-workshop.github.io

Call for Papers | MUWS 2026

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Reposted by Jing Yang

Nils Feldhus @nfel.bsky.social · 19/03/2026

Can Persona Prompting function as a lens on social reasoning? In our #EACL2026 work (led by @jingyng.bsky.social), we investigate how it impacts the quality of model outputs and rationales. 🗞️ arXiv: arxiv.org/abs/2601.20757 Come and find us (Jing, Moritz, Elisabeth, myself) in 🇲🇦 Rabat next week!

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Reposted by Jing Yang

UKP Lab @ukplab.bsky.social · 25/07/2025

Can LLMs generate explanations for datasets without such annotations? 🧠 We tested model explanations across 19 datasets (NLI, fact-checking, hallucination detection) to see how well they self-rationalize on completely unseen data. #LLMs #Explainability #ACL2025 #TACL

OOD evaluation pipeline of self-rationalization, and OOD datasets categories considered in the paper.

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