2 citations · 3 across the 9 of their papers we have counts for
10 papers
BeliefGraph-JEPA: Structured Latent World Models for Action-Conditioned Time Series
Yue Li, Kangqi Ni, Zhen Tan +1
Action-conditioned time-series forecasting requires accounting for how future actions and exogenous forcings influence multiple targets through partially observed effects with diff…
EndoMD-SLAM: Endoscopic Gaussian Splatting SLAM under Optical Degradation with Memory and Static-Transient Decomposition
Nuo Chen, Kangqi Ni, Lulin Liu +5
Dense 3D reconstruction is critical for clinical endoscopic navigation and documentation. While Gaussian Splatting SLAM systems show promise in this domain, they fundamentally rely…
Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
Zhuoxuan Zhang, Kangqi Ni, Yuhang Chen +12
Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-ordering a candidate list, but they are slow at inference: an autore…
OpenComputer: Verifiable Software Worlds for Computer-Use Agents
Jinbiao Wei, Qianran Ma, Yilun Zhao +4
We present OpenComputer, a verifier-grounded framework for constructing verifiable software worlds for computer-use agents. OpenComputer integrates four components: (1) app-specifi…
Step-level Optimization for Efficient Computer-use Agents
Jinbiao Wei, Kangqi Ni, Yilun Zhao +2
Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfaces instead of relying on br…
Chimera: Latency- and Performance-Aware Multi-agent Serving for Heterogeneous LLMs
Kangqi Ni, Wenyue Hua, Xiaoxiang Shi +3
Multi-agent applications often execute complex tasks as multi-stage workflows, where each stage is an LLM call whose output becomes part of context for subsequent steps. Existing L…
ANCHOR: Branch-Point Data Generation for GUI Agents
Jinbiao Wei, Yilun Zhao, Kangqi Ni +1
End-to-end GUI agents for real desktop environments require large amounts of high-quality interaction data, yet collecting human demonstrations is expensive and existing synthetic…
Can GRPO Help LLMs Transcend Their Pretraining Origin?
Kangqi Ni, Zhen Tan, Zijie Liu +2
Reinforcement Learning with Verifiable Rewards (RLVR), primarily driven by the Group Relative Policy Optimization (GRPO) algorithm, is a leading approach for enhancing the reasonin…
Automated Long Answer Grading with RiceChem Dataset
Shashank Sonkar, Kangqi Ni, Lesa Tran Lu +3
We introduce a new area of study in the field of educational Natural Language Processing: Automated Long Answer Grading (ALAG). Distinguishing itself from Automated Short Answer Gr…
Pedagogical Alignment of Large Language Models
Shashank Sonkar, Kangqi Ni, Sapana Chaudhary +1
Large Language Models (LLMs), when used in educational settings without pedagogical fine-tuning, often provide immediate answers rather than guiding students through the problem-so…