21 citations · 69 across the 11 of their papers we have counts for
11 papers
DiffImaginE: Imagine to Verify Entity Types with Diffusion
Feng Zhang, Feiyu Han, Rongxin Yang +11
Multimodal named entity recognition (MNER) determines whether each candidate span and entity-type hypothesis is supported by joint textual and visual evidence. Existing imagine-and…
Physiological World Models for Human State Transitions
Chongyang Zhang, Rendong Wang, Hao Zheng +4
Continuous multimodal sensing now allows human physiology to be observed throughout daily life rather than only during occasional clinical visits. However, most health artificial i…
Thought-Aware KV Cache Compaction for Reasoning via Adaptive Attention Matching
Yang Liu, Bin Chong, Chongyang Zhang +3
Reasoning language models generate lengthy chain-of-thought (CoT) sequences whose key-value (KV) cache grows linearly and becomes a memory bottleneck during decoding. Existing comp…
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification
Hao Zheng, Runqi Wang, Jianzhuang Liu +1
The conventional few-shot classification aims at learning a model on a large labeled base dataset and rapidly adapting to a target dataset that is from the same distribution as the…
Gait Cycle-Inspired Learning Strategy for Continuous Prediction of Knee Joint Trajectory from sEMG
Xueming Fu, Hao Zheng, Luyan Liu +9
Predicting lower limb motion intent is vital for controlling exoskeleton robots and prosthetic limbs. Surface electromyography (sEMG) attracts increasing attention in recent years…
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
Hao Zheng, Regina Lee, Yuqian Lu
Understanding comprehensive assembly knowledge from videos is critical for futuristic ultra-intelligent industry. To enable technological breakthrough, we present HA-ViD - the firs…
Caption Anything: Interactive Image Description with Diverse Multimodal Controls
Teng Wang, Jinrui Zhang, Junjie Fei +5
Controllable image captioning is an emerging multimodal topic that aims to describe the image with natural language following human purpose, , looking at the specifi…
Real-World Compositional Generalization with Disentangled Sequence-to-Sequence Learning
Hao Zheng, Mirella Lapata
Compositional generalization is a basic mechanism in human language learning, which current neural networks struggle with. A recently proposed Disentangled sequence-to-sequence mod…
Disentangled Sequence to Sequence Learning for Compositional Generalization
Hao Zheng, Mirella Lapata
There is mounting evidence that existing neural network models, in particular the very popular sequence-to-sequence architecture, struggle to systematically generalize to unseen co…
Compositional Generalization via Semantic Tagging
Hao Zheng, Mirella Lapata
Although neural sequence-to-sequence models have been successfully applied to semantic parsing, they fail at compositional generalization, i.e., they are unable to systematically g…
Sentence Centrality Revisited for Unsupervised Summarization
Hao Zheng, Mirella Lapata
Single document summarization has enjoyed renewed interests in recent years thanks to the popularity of neural network models and the availability of large-scale datasets. In this…