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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.LG2026

Kalman Meets Curriculum: Efficient Dynamic Prompt Selection for Adaptive RL Finetuning

Haodong Zhu, Yangyang Ren, Yanjing Li +4

The paper introduces Kalman-Guided Prompt Selection (KGPS), a method that treats prompt difficulty as a dynamic state estimated with a Kalman filter to adaptively choose prompts du…

cs.CV2026

InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection

Zichao Feng, Haodong Zhu, Jingying Yang +8

Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based methods typically require both R…

cs.LG2026

Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization

Haodong Zhu, Yangyang Ren, Yanjing Li +6

Group Relative Policy Optimization (GRPO) effectively scales LLM reasoning but incurs prohibitive computational costs due to its extensive group-based sampling requirement. While r…

cs.GR2025

Surf3R: Rapid Surface Reconstruction from Sparse RGB Views in Seconds

Haodong Zhu, Changbai Li, Yangyang Ren +5

Current multi-view 3D reconstruction methods rely on accurate camera calibration and pose estimation, requiring complex and time-intensive pre-processing that hinders their practic…

cs.CV2025

WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detection

Haodong Zhu, Wenhao Dong, Linlin Yang +10

Leveraging the complementary characteristics of visible (RGB) and infrared (IR) imagery offers significant potential for improving object detection. In this paper, we propose WaveM…

cs.LG2025

Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method

Qingcheng Zhu, Yangyang Ren, Linlin Yang +9

Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can significantly reduce storage and…