Papers by Qihang Zhang

5 papers
Boosting Multi-modal Keyphrase Prediction with Dynamic Chain-of-Thought in Vision-Language Models (2025.emnlp-main)

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Challenge: Multi-modal keyphrase prediction (MMKP) aims to produce concise, informative phrases that capture the essence of cross-modal inputs.
Approach: They propose to use vision-language models to generate conclusive phrases using multiple modalities of input information.
Outcome: The proposed methods outperform existing methods on absence and unseen scenarios and overestimate model capability due to overlap in training tests.
Test-Time Steering for Lossless Text Compression via Weighted Product of Experts (2025.findings-emnlp)

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Challenge: gzip and neural compression models often lead to poor performance in unseen data.
Approach: They propose a framework that performs Test-Time Steering via a Weighted Product of Experts (wPoE)
Outcome: The proposed framework performs Test-Time Steering via a Weighted Product of Experts (wPoE) it integrates with any autoregressive language model, providing a practical solution for enhancing text compression across diverse data distributions.
Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation (2020.aacl-main)

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Challenge: Existing methods for transferring knowledge from BERT into a model with large parameters are not efficient due to their large-scale and high computational cost.
Approach: They propose a sentence representation approximating oriented distillation framework that can distill pre-trained BERT into a simple LSTM based model without specifying tasks.
Outcome: The proposed model outperforms other distillation methods and larger models on multiple NLP tasks with efficiency well-improved.
Sudowoodo: A Chinese Lyric Imitation System with Source Lyrics (2023.emnlp-demo)

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Challenge: Existing studies on lyrics generation focus on generating accurate lyrics using keywords, rhymes, etc. However, there is no parallel corpus for lyrics imitation.
Approach: They propose a Chinese lyrics imitation system that can generate new lyrics based on source lyrics.
Outcome: The proposed system can generate new lyrics based on the source lyrics . human evaluation shows it can perform better lyric imitation.
Mobile-R1: Towards Interactive Capability for VLM-Based Mobile Agent via Systematic Training (2026.acl-long)

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Challenge: Existing approaches to training agents for visual-language models trap them in local optima, hindering exploration and error correction with the environment.
Approach: They propose a hierarchical training recipe that bridges atomic action execution and strategic task completion.
Outcome: The proposed training recipe bridges atomic action execution and strategic task completion.

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