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20222026
most citedImproving Hateful Meme Detection through Retrieval-Guided Contrastive Learning

23 citations · 49 across the 11 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization

Guangyu Yang, Jingbiao Mei, Mingsheng Sun +5

The rapid growth of video-based social media has increased users' exposure to harmful content, creating a need for reliable automated video safety detection. Although recent Vision…

cs.CL2026

BERAG: Bayesian Ensemble Retrieval-Augmented Generation for Knowledge-based Visual Question Answering

Jinghong Chen, Jingbiao Mei, Guangyu Yang +1

A common approach to question answering with retrieval-augmented generation (RAG) is to concatenate documents into a single context and pass it to a language model to generate an a…

cs.CL2025

ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection

Jingbiao Mei, Mingsheng Sun, Jinghong Chen +4

Hateful memes have emerged as a particularly challenging form of online abuse, motivating the development of automated detection systems. Most prior approaches rely on direct detec…

cs.CL2025★ 7 cited

Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection

Jingbiao Mei, Jinghong Chen, Guangyu Yang +2

Hateful memes have become a significant concern on the Internet, necessitating robust automated detection systems. While Large Multimodal Models (LMMs) have shown promise in hatefu…

cs.CL2024

On Extending Direct Preference Optimization to Accommodate Ties

Jinghong Chen, Guangyu Yang, Weizhe Lin +2

We derive and investigate two DPO variants that explicitly model the possibility of declaring a tie in pair-wise comparisons. We replace the Bradley-Terry model in DPO with two wel…

cs.CL2024

Control-DAG: Constrained Decoding for Non-Autoregressive Directed Acyclic T5 using Weighted Finite State Automata

Jinghong Chen, Weizhe Lin, Jingbiao Mei +1

The Directed Acyclic Transformer is a fast non-autoregressive (NAR) model that performs well in Neural Machine Translation. Two issues prevent its application to general Natural La…

cs.CL2024

PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers

Weizhe Lin, Jingbiao Mei, Jinghong Chen +1

Large Multimodal Models (LMMs) excel in natural language and visual understanding but are challenged by exacting tasks such as Knowledge-based Visual Question Answering (KB-VQA) wh…

cs.CL2023★ 23 cited

Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learning

Jingbiao Mei, Jinghong Chen, Weizhe Lin +2

Hateful memes have emerged as a significant concern on the Internet. Detecting hateful memes requires the system to jointly understand the visual and textual modalities. Our invest…

cs.CL2023★ 9 cited

Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering

Weizhe Lin, Jinghong Chen, Jingbiao Mei +2

Knowledge-based Visual Question Answering (KB-VQA) requires VQA systems to utilize knowledge from external knowledge bases to answer visually-grounded questions. Retrieval-Augmente…