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Home/Authors/Tong Wu

Tong Wu

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

NLP×2Crypto×2Vision×1AI×1Comp. Eng.×1Society×1Computational Finance×1

Frequent co-authors

Xiaobo Wang1×
Min Tang1×
Jiaqi Li1×
Qi Liu1×
Zilong Zheng1×
Xinyu Yan1×

Research Timeline

2026
Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

This study uses a BERT-based LLM to analyze Discord sentiment and combines it with financial data to build a multi-modal model that significantly improves the prediction of Decentraland's MANA token price.

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

The paper introduces FraudBench, a multimodal benchmark designed to detect AI-generated fraudulent refund evidence, finding that current AI models struggle significantly with claim-conditioned fake-damage detection.

The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement

The paper introduces SAVE, a framework that uses on-policy feedback and the value function to self-supervise and improve reward models, significantly enhancing RLHF performance across multiple benchmarks.

Highlighted terms show continued research focus across papers

Papers

cs.CLRecentMay 29, 2026

The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement

Xiaobo Wang, Tong Wu, Min Tang, Jiaqi Li +2 more

The paper introduces SAVE, a framework that uses on-policy feedback and the value function to self-supervise and improve reward models, significantly enhancing RLHF performance across multiple benchma…

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cs.CVcs.AIcs.CRRecentMay 9, 2026

FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

Xinyu Yan, Boyang Chen, Jiaming Zhang, Tiantong Wu +11 more

The paper introduces FraudBench, a multimodal benchmark designed to detect AI-generated fraudulent refund evidence, finding that current AI models struggle significantly with claim-conditioned fake-da…

View →
cs.CLcs.CEcs.CRRecentApr 4, 2026

Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

Xintong Wu, Peiting Tsai, Jing Yuan, Michael Yu +2 more

This study uses a BERT-based LLM to analyze Discord sentiment and combines it with financial data to build a multi-modal model that significantly improves the prediction of Decentraland's MANA token p…

View →