AI Agent Papers2026
Sihan Ge, Yichen Lin +4Affiliation: Cardinal Operations, Affiliation: Shanghai Jiao Tong University, Shanghai, China
[email protected] {linyichen, chenyuzhou, linjianghao, taoyao, ddge}@sjtu.edu.cn
* Equal contribution † Corresponding authors
Studies when and how an assistant should ask clarification questions before converting natural-language problem descriptions into optimization models. Introduces OR-Clarify, a benchmark for pre-formulation clarification, and InterOPT, a two-stage framework that diagnoses formulation-critical gaps and guides targeted questioning and stopping decisions.
Generates compositional 3D scenes as collections of individual object meshes by conditioning a single-object 3D generative prior on multi-view posed observations. Key features include anchor-aligned canonical frames, multi-view DINOv3 feature lifting with an IBR-style fusion, and LoRA adaptation to complete heavily occluded objects; includes a large UE-MeshyScene benchmark.