Papers by Xiaoyong Du

6 papers
TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities (2023.acl-demo)

Copied to clipboard

Challenge: Several pre-training models of different modalities are showing a rising trend of homogeneity in their model structures.
Approach: They propose a toolkit that supports pre-training models of different modalities.
Outcome: The proposed toolkit can match the performance of the original implementations on text, vision, and audio benchmarks.
Double-Edged Sword or Sharp Tool? Designing and Evaluating Triadic LLM-Teacher Collaboration for K-12 Writing at Scale (2026.findings-acl)

Copied to clipboard

Challenge: a large-scale empirical dataset involving 57,954 essays from 10,195 students across 120 schools over two years is presented in this paper.
Approach: They propose a triadic collaboration system that supports K-12 writing learning . they propose linguistic expansion as a pedagogical gatekeeper and bridge .
Outcome: The proposed system improves writing quality through a strategic labor division . authors find that excessive linguistic expansion yields diminishing marginal utility .
PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training (2022.emnlp-main)

Copied to clipboard

Challenge: Table-based fact verification has attracted a lot of attention recently due to the lack of datasets that can be used to pre-train language models to be aware of common table operations.
Approach: They propose a table-based fact verification tool that pre-trains language models to be aware of common table operations such as aggregating a column or comparing tuples.
Outcome: The proposed method outperforms previous methods on two table-based fact verification datasets TabFact and SEM-TAB- FACTS.
UER: An Open-Source Toolkit for Pre-training Models (D19-3)

Copied to clipboard

Challenge: Existing work on pre-training models have shown that it is important to use a framework to deploy various pre- training models efficiently.
Approach: They propose an assemble-on-demand pre-training toolkit that assembles pre-trained models on demand and encapsulates them with rich modules.
Outcome: The proposed framework can reproduce state-of-the-art models or develop models that remain unexplored.
Enabling Agents to Communicate Entirely in Latent Space (2026.acl-long)

Copied to clipboard

Challenge: Natural language is the de facto communication medium for LLM-based agents, but it presents a fundamental constraint . natural language downsampling limits the depth and nuance of information that can be transmitted . et al.: inter-agent latent space communication is a promising paradigm for solving complex tasks .
Approach: They propose a paradigm that leverages the last hidden states of an LLM as a representation of its thought for direct communication.
Outcome: The proposed paradigm outperforms fine-tuned chain-of-thought prompting and single-agent baselines even across heterogeneous models.
Analogical Reasoning on Chinese Morphological and Semantic Relations (P18-2)

Copied to clipboard

Challenge: Analogical reasoning is effective in capturing linguistic regularities.
Approach: They propose to use Chinese lexical knowledge to build an analogical reasoning task using a large dataset.
Outcome: The proposed dataset proves to be reliable benchmark for evaluating Chinese word embeddings.

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