PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast
本文提出PCSDiff框架，通过扩散模型和多分支解码器解决中长期降水预报中的系统偏差、误差累积及分辨率低的问题，提高预报准确性。
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研究通过引入GazeFS方法，基于视线-头部历史预测和稳定目标中心的视线轨迹，以改善目标获取时的视线精准度与稳定性。
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Automated Analysis Framework for Multilingual Climate-Health Literature Based on Multi-Agent Large Language Model
为解决多语言气候-健康文献分析效率低的问题，提出基于多代理大型语言模型的自动化分析框架，实现文献筛选、信息提取和标准化整合全过程自动化。
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CacheRouter: A Dual-Path Tool Routing Architecture with Cache-Preserving Main-Model Isolation for Long-Tail Tool Discovery
为解决LLM系统中工具使用的结构权衡问题，提出了一种双路径路由架构CacheRouter，通过分离工具选择和交付通道，保持主模型请求前缀稳定，提高缓存命中率。
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InterPruner: Interactive Structured Pruning via Taylor-Implicit Criterion and Language-Prior Modulator for Multimodal Object Detection
This work addresses the challenges of channel redundancy and high computational cost in RGB-infrared multimodal object detection arising from parallel feature extraction, where existing pruning methods overlook cross-modal interactions and scene-level dynamic redundancy. To this end, we propose the first interactive structured channel pruning framework tailored for this task, which innovatively integrates three key components: a Taylor-based implicit criterion to quantify channel importance, a Modality Interaction Redundancy Analysis (MIRA) module to model cross-modal complementarity, and a language prior-guided Scene-level Pruning with Contextual Awareness (SPCA) mechanism to enable dynamic, context-aware channel pruning. Evaluated on the FLIR dataset, our method achieves a 0.6% increase in mAP after pruning 50% of channels, demonstrating simultaneous reductions in computational overhead and improvements—or at least preservation—of detection performance.
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PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast
本文提出PCSDiff框架，通过扩散模型和多分支解码器解决中长期降水预报中的系统偏差、误差累积及分辨率低的问题，提高预报准确性。
0 citationsRead paper
GazeFS: Target-Centered Gaze-Trajectory Forecasting and Stabilization from Gaze-Head History
研究通过引入GazeFS方法，基于视线-头部历史预测和稳定目标中心的视线轨迹，以改善目标获取时的视线精准度与稳定性。
0 citationsRead paper
Automated Analysis Framework for Multilingual Climate-Health Literature Based on Multi-Agent Large Language Model
为解决多语言气候-健康文献分析效率低的问题，提出基于多代理大型语言模型的自动化分析框架，实现文献筛选、信息提取和标准化整合全过程自动化。
0 citationsRead paper
CacheRouter: A Dual-Path Tool Routing Architecture with Cache-Preserving Main-Model Isolation for Long-Tail Tool Discovery
为解决LLM系统中工具使用的结构权衡问题，提出了一种双路径路由架构CacheRouter，通过分离工具选择和交付通道，保持主模型请求前缀稳定，提高缓存命中率。
0 citationsRead paper
InterPruner: Interactive Structured Pruning via Taylor-Implicit Criterion and Language-Prior Modulator for Multimodal Object Detection
This work addresses the challenges of channel redundancy and high computational cost in RGB-infrared multimodal object detection arising from parallel feature extraction, where existing pruning methods overlook cross-modal interactions and scene-level dynamic redundancy. To this end, we propose the first interactive structured channel pruning framework tailored for this task, which innovatively integrates three key components: a Taylor-based implicit criterion to quantify channel importance, a Modality Interaction Redundancy Analysis (MIRA) module to model cross-modal complementarity, and a language prior-guided Scene-level Pruning with Contextual Awareness (SPCA) mechanism to enable dynamic, context-aware channel pruning. Evaluated on the FLIR dataset, our method achieves a 0.6% increase in mAP after pruning 50% of channels, demonstrating simultaneous reductions in computational overhead and improvements—or at least preservation—of detection performance.
0 citationsRead paper