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20242026
most citedDual-level Mixup for Graph Few-shot Learning with Fewer Tasks

4 citations · 6 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.CL2026

TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning

Xiaosong Han, Ke Chen, Xindi Dai +7

In real-world deployment, LLMs are often adapted continually across tasks to keep LLMs up-to-date in production, where new fine-tuning should preserve previously learned skills. Ho…

cs.CL2025

Variety Is the Spice of Life: Detecting Misinformation with Dynamic Environmental Representations

Bing Wang, Ximing Li, Yiming Wang +4

The proliferation of misinformation across diverse social media platforms has drawn significant attention from both academic and industrial communities due to its detrimental effec…

cs.CL2025

Robust Misinformation Detection by Visiting Potential Commonsense Conflict

Bing Wang, Ximing Li, Changchun Li +4

The development of Internet technology has led to an increased prevalence of misinformation, causing severe negative effects across diverse domains. To mitigate this challenge, Mis…

cs.CL2025

A Simple Graph Contrastive Learning Framework for Short Text Classification

Yonghao Liu, Fausto Giunchiglia, Lan Huang +3

Short text classification has gained significant attention in the information age due to its prevalence and real-world applications. Recent advancements in graph learning combined…

cs.CL2025

Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive Learning

Yonghao Liu, Mengyu Li, Wei Pang +4

Short text classification, as a research subtopic in natural language processing, is more challenging due to its semantic sparsity and insufficient labeled samples in practical sce…

cs.CL2024

Harmfully Manipulated Images Matter in Multimodal Misinformation Detection

Bing Wang, Shengsheng Wang, Changchun Li +2

Nowadays, misinformation is widely spreading over various social media platforms and causes extremely negative impacts on society. To combat this issue, automatically identifying m…