Announcement_13

🔔 Excited to share that our works on (i) ExGra-Med — a data-efficient multimodal large language model (LLM) for healthcare; (ii) Token Redundancy in 3D Point Cloud Transformers — uncovering how existing 3D transformers (e.g., Ptv-3, Sonata) are over-tokenized, and proposing an efficient token merging strategy that reduces computation by up to 90-95% while preserving accuracy; and (iii) Over-Optimization in RLHF for LLM Post-Training — exploring how reinforcement learning from human feedback can lead to alignment instability and proposing new insights into optimization LLM post-training have been accepted to NeurIPS 2025 🎉. Excited to present and discuss them at San Diego 🇺🇸 🚀