Our team: MohammadHossein Rezaei (@mhrezaeics), Robert Vacareanu (@robert_nlp), Zihao Wang (@wzihao12), Clinton Wang (@clintonjwang), Yunzhong He (@_yunzhong), Feyza Akyürek (@afeyzaakyurek) Paper: arxiv.org/pdf/2510.07284
Unfortunately, I had to miss out on attending in person in Vienna, but glad to see the recognition. We need more research on understanding data and posttraining of LLMs. Always a pleasure working with @alan and @JunmoKang
🎉 Excited to see that our paper on cost-efficient data annotation for LLMs won an SAC Highlight Award! 🔗 Check out @mohit_rag18's work here: aclanthology.org/2025.acl-long.…
🤔 How do we train LLMs on real-world tasks where it’s hard to define a single verifiable answer? Our work at @scale_AI introduces Rubrics as Rewards (RaR) — a framework for on-policy post-training that uses structured, checklist-style rubrics as interpretable reward signals. 🧵
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