activity
20232026
most citedLabel Supervised LLaMA Finetuning

20 citations · 21 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning

Xianming Li, Zongxi Li, Tsz-fung Andrew Lee +3

Popular low-rank parameter-efficient fine-tuning (PEFT) methods represent adaptation as separate updates to selected backbone weights, without maintaining an explicit task-specific…

cs.CL2025

HI-TransPA: Hearing Impairments Translation Personal Assistant

Zhiming Ma, Shiyu Gan, Junhao Zhao +10

Hearing-impaired individuals often face significant barriers in daily communication due to the inherent challenges of producing clear speech. To address this, we introduce the Omni…

cs.CL2025

OASIS: Order-Augmented Strategy for Improved Code Search

Zuchen Gao, Zizheng Zhan, Xianming Li +6

Code embeddings capture the semantic representations of code and are crucial for various code-related large language model (LLM) applications, such as code search. Previous trainin…

cs.CL2024

2D Matryoshka Sentence Embeddings

Xianming Li, Zongxi Li, Jing Li +2

Common approaches rely on fixed-length embedding vectors from language models as sentence embeddings for downstream tasks such as semantic textual similarity (STS). Such methods ar…

cs.CL2024

Generative Deduplication For Socia Media Data Selection

Xianming Li, Jing Li

Social media data exhibits severe redundancy caused by its noisy nature. It leads to increased training time and model bias in its processing. To address this issue, we propose a n…

cs.CL2023

BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings

Xianming Li, Jing Li

Sentence embeddings are crucial in measuring semantic similarity. Most recent studies employed large language models (LLMs) to learn sentence embeddings. Existing LLMs mainly adopt…