HRScene: How Far Are VLMs from Effective High-Resolution Image Understanding? "we introduce HRScene, a novel unified benchmark for HRI understanding with rich scenes. HRScene incorporates 25 real-world datasets and 2 synthetic diagnostic datasets with resolutions ranging from

As Vision Language Models treat images as tokens, high-resolution images create long sequences, similar to long-context challenges in LLMs. In this new paper, we release a benchmark to test VLMs capabilities to understand high-resolution images, up to hundreds of millions of

This work is led by my first PhD student Yusen Yusen Zhang, who is graduating soon and actively seeking a postdoc position in academia. It has been an absolute pleasure to work with him. Please consider hiring him!

🎉Our paper on fairness of multidoc summarization has received an SAC award at NAACL 2025! 🥳 We appreciate the recognition from senior area chairs. Haoyuan Li and Yusen Zhang will present our work: Posters (Exhibit Hall), Session H: Oral/Poster 5, Thursday May 1,

Excited to share that I’ll be starting a research internship at Microsoft in Redmond! Looking forward to the research ahead and meeting people in Seattle/Redmond!

excited to finally share on arxiv what we've known for a while now: All Embedding Models Learn The Same Thing embeddings from different models are SO similar that we can map between them based on structure alone. without *any* paired data feels like magic, but it's real:🧵

Excited to share our latest work! The development of process reward models (PRMs) is limited by manual labeling of step-level reasoning correctness. In this new paper led by Ryo Kamoi, we use formal verification tools — formal logic and theorem proving — to automatically

How can we improve the fairness of multi-document summarization (MDS). We propose FairPO, a preference tuning method that improve fairness using perturbation-based preference pair generation and fairness-aware preference tuning. Paper accepted by #ACL2025. (1/5)

Congratulations Vipul Gupta !!!🎉

Another awesome work on improving fairness in summarization led by Haoyuan Li and in collaboration with Rui Zhang. Haoyuan will be presenting it at #ACL25 @uncnlp

HRScene got accepted at #ICCV2025! HRScene is a novel unified benchmark for high-resolution image understanding with 25 scenes and 2 NIAH tests. Home page: yszh8.github.io/hrscene/ (Sorry, EvalAI for submission does not work currently...) My PhD research began with long text

Our paper VisOnlyQA has been accepted to Conference on Language Modeling #COLM2025! See you in Montreal🍁 We find that even recent Vision Language Models struggle with simple questions about geometric properties in images, such as "What is the degree of angle AOD?"🧐 arxiv.org/abs/2412.00947

new blog post "All AI Models Might Be The Same" in which i explain the Platonic Representation Hypothesis, the idea behind universal semantics, and we might use AI to understand whale speech and decrypt ancient texts

Will be attending #ACL2025. Happy to talk about the two papers being presented from our lab on (1) Identifying unreliable narrators w Anneliese Brei Shashank Srivastava (2) Improving fairness in multi-document summarization w Haoyuan Li Rui Zhang @uncnlp

Congratulations to this year's deserving winner, whose dedication has significantly shaped our field! Their service is an inspiration to us all. ✨ #ACL2025NLP #DistinguishedServiceAward #CompLing #Community

🕊️ Lifetime Achievement Award at #ACL2025NLP A standing ovation for Prof. Kathy McKeown, recipient of the ACL 2025 Lifetime Achievement Award! 🌟

Unbelievable that this is the loss we are optimizing for "intelligence".

How are researchers optimizing AI systems for science? CSRAI Affiliate Rui Zhang from Penn State EECS shares how to improve the efficiency and usefulness of AI and some strategies individuals can employ to get more value out of their personal AI use. psu.edu/news/engineeri…

📢 NewSumm Workshop at EMNLP 2025 is now open for submissions! In 2023, the workshop attracted a large audience, and we’re excited to welcome more great work and discussions this year. 📝✨ Don’t miss the great opportunity to present your work!