Papers by Yuanchi Zhang

6 papers
ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models (2025.acl-long)

Copied to clipboard

Challenge: Existing benchmarks for evaluating MLLMs have not addressed active perception . a novel benchmark is proposed to evaluate active perception in ML models .
Approach: They propose a benchmark to evaluate active perception in Multimodal Large Language Models . they restrict the perceptual field of a model and require it to actively zoom or shift it .
Outcome: The proposed benchmark focuses on a specialized form of Visual Question Answering (VQA) that eases and quantifies the evaluation yet challenging for existing MLLMs.
Perspective Transition of Large Language Models for Solving Subjective Tasks (2025.findings-acl)

Copied to clipboard

Challenge: Large language models (LLMs) have revolutionized the field of natural language processing . performance of LLMs on subjective tasks is limited, authors say .
Approach: They propose a method that allows LLMs to select between direct, role, and third-person perspectives for best way to solve corresponding subjective problem.
Outcome: The proposed method outperforms widely used single fixed perspective based methods on 12 subjective tasks.
DirectQuote: A Dataset for Direct Quotation Extraction and Attribution in News Articles (2022.lrec-1)

Copied to clipboard

Challenge: Existing methods to extract and attribute quotations from news data are difficult and require a lot of effort.
Approach: They propose a corpus of 19,760 paragraphs and 10,279 direct quotations manually annotated from online news media.
Outcome: The proposed corpus contains 19,760 paragraphs and 10,279 direct quotations manually annotated from online news media.
Continual Knowledge Distillation for Neural Machine Translation (2023.acl-long)

Copied to clipboard

Challenge: Current parallel corpora are not publicly accessible but trained models are more readily available.
Approach: They propose a method to take advantage of existing translation models to improve one model of interest.
Outcome: The proposed method improves on Chinese-English and German-English datasets and is robust to malicious models.
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages (2024.acl-long)

Copied to clipboard

Challenge: Contemporary large language models (LLMs) are pre-trained on multilingual corpora, but their performance lags behind in most languages compared to a few resource-rich languages.
Approach: They propose a method that leverages the internal capabilities of large language models on resource-rich languages to enhance multilingual performance.
Outcome: The proposed method improves multilingual performance while minimizing impact on original performance in resource-rich languages.
Boundary Matters: Leveraging Structured Text Plots for Long Text Outline Generation (2025.findings-emnlp)

Copied to clipboard

Challenge: Existing methods for generating readable outlines are inability to segment long texts .
Approach: They propose an unsupervised framework to guide large language model outline generation . framework ensures each structured plot encapsulates complete causality by accurately identifying plot boundaries.
Outcome: The proposed framework ensures that each structured plot encapsulates complete causality by accurately identifying plot boundaries.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations