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Peng Peng

5 accepted papers

2026

PROMISE: Prompt-Attentive Hierarchical Contrastive Learning for Robust Cross-Modal Representation with Missing Modalities

AAAI 2026technical

Multimodal models integrating natural language and visual information have substantially improved emotion recognition performance. However, their effectiveness significantly declines in real-world situations where certain modalities are missing or unavailable. This degradation primarily stems from i

Cited by 0SourcePDFScholar
2026

SURE-MED: SYSTEMATIC UNCERTAINTY REDUCTION FOR ENHANCED RELIABILITY IN MEDICAL REPORT GENERATION

ICASSP 2026poster

Automated medical report generation (MRG) holds great promise for reducing the heavy workload of radiologists. However, its clinical deployment is hindered by three major sources of uncertainty. First, visual uncertainty, caused by noisy or incorrect view annotations, compromises feature extraction.…

Cited by 0SourcePDFScholar
2023

A Class-Rebalancing Self-Training Framework for Distantly-Supervised Named Entity Recognition

ACL 2023findings

Distant supervision reduces the reliance on human annotation in the named entity recognition tasks. The class-level imbalanced distant annotation is a realistic and unexplored problem, and the popular method of self-training can not handle class-level imbalanced learning. More importantly, self-trai…

2022

Obstacle Avoidance of Resilient UAV Swarm Formation with Active Sensing System in the Dense Environment

IROS 2022poster

This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First, the point cloud received by each UAV is fit by the gaussian mixture model (GMM) and transmitted in the swarm. Resampli…

Cited by 21SourceScholar
2021

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

ICML 2021spotlight

AlphaStar, the AI that reaches GrandMaster level in StarCraft II, is a remarkable milestone demonstrating what deep reinforcement learning can achieve in complex Real-Time Strategy (RTS) games. However, the complexities of the game, algorithms and systems, and especially the tremendous amount of com…