9 papers
Iris: Climbing to the Search Frontier
Ziyuan Liu, Hengqi Liu, Zichuan Wang +8
We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse…
Recovering General Capabilities via Uncertainty-Calibrated Multi-Teacher On-Policy Distillation
Ziyuan Liu, Jiao Ou, Jian Liang +2
Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities. We study this trade-off in Multi-Teacher On-Policy…
Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling
Qitan Shi, Cheng Jin, Ziyuan Liu +1
Few-step distilled diffusion models generate high-quality images quickly, but often lose per-prompt diversity, producing near-identical samples across random seeds. Optimizing the…
JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answering
Ziyuan Liu, Ruifei Zhu, Ouqiao Ma +1
Remote sensing change detection (CD) traditionally focuses on pixel-level binary segmentation, which identifies where changes occur but neither what nor why. To bridge this semanti…
Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
Jiawei Zhang, Ziyuan Liu, Leon Yan +2
The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between distortion performance and perce…
Counteraction-Aware Multi-Teacher On-Policy Distillation for General Capability Recovery with Domain Preservation
Tianlei Chen, Jiao Ou, Ziyuan Liu +3
Domain specialization can improve LLM behavior, but often weakens the general capabilities inherited from the original model. Recent Multi-Teacher On-Policy Distillation (MOPD) pip…
MCD: A Unified MultiModal Framework for Optical-SAR Change Detection with Mixture of Experts and Self-Distillation
Ziyuan Liu, Jiawei Zhang, Wenyu Wang +1
Most existing change detection (CD) methods focus on optical images captured at different times, and deep learning (DL) has achieved remarkable success in this domain. However, in…
Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Learnable Linear Extrapolation
Jiawei Zhang, Ziyuan Liu, Leon Yan +2
Diffusion-based inverse algorithms have shown remarkable performance across various inverse problems, yet their reliance on numerous denoising steps incurs high computational costs…
JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework
Ziyuan Liu, Ruifei Zhu, Long Gao +3
Change detection (CD) in remote sensing images plays a vital role in Earth observation. However, the scarcity of high-resolution, comprehensive open-source datasets and the difficu…