3 papers
cs.LG2026
Group Cognition Learning: Making Everything Better Through Governed Two-Stage Agents Collaboration
Chunlei Meng, Pengbin Feng, Rong Fu +7
Centralized multimodal learning commonly compresses language, acoustic, and visual signals into a single fused representation for prediction. While effective, this paradigm suffers…
cs.CV2026
EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory
Yuyang Li, Yime He, Zeyu Zhang +1
Long-term conversational memory requires retrieving evidence scattered across multiple sessions, yet single-pass retrieval fails on temporal and multi-hop questions. Existing itera…
cs.DC2025
ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao +9
Large multimodal models (LMMs) demonstrate impressive capabilities in understanding images, videos, and audio beyond text. However, efficiently serving LMMs in production environme…