most citedSEAL-Tag: Self-Tag Evidence Aggregation with Probabilistic Circuits for PII-Safe Retrieval-Augmented Generation

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

TABQAWORLD: Optimizing Multimodal Reasoning for Multi-Turn Table Question Answering

Tung Sum Thomas Kwok, Xinyu Wang, Xiaofeng Lin +7

Multimodal reasoning has emerged as a powerful framework for enhancing reasoning capabilities of reasoning models. While multi-turn table reasoning methods have improved reasoning…

cs.LG2026

SYNTHONY: A Stress-Aware, Intent-Conditioned Agent for Deep Tabular Generative Models Selection

Hochan Son, Xiaofeng Lin, Jason Ni +1

Deep generative models for tabular data (GANs, diffusion models, and LLM-based generators) exhibit highly non-uniform behavior across datasets; the best-performing synthesizer fami…

cs.CR20261 cited

SEAL-Tag: Self-Tag Evidence Aggregation with Probabilistic Circuits for PII-Safe Retrieval-Augmented Generation

Jin Xie, Songze Li, Guang Cheng

Retrieval-Augmented Generation (RAG) systems introduce a critical vulnerability: contextual leakage, where adversaries exploit instruction-following to exfiltrate Personally Identi…

cs.CL2025

Bridging the Language Gap: Synthetic Voice Diversity via Latent Mixup for Equitable Speech Recognition

Wesley Bian, Xiaofeng Lin, Guang Cheng

Modern machine learning models for audio tasks often exhibit superior performance on English and other well-resourced languages, primarily due to the abundance of available trainin…

cs.CR2025

Synth-MIA: A Testbed for Auditing Privacy Leakage in Tabular Data Synthesis

Joshua Ward, Xiaofeng Lin, Chi-Hua Wang +1

Tabular Generative Models are often argued to preserve privacy by creating synthetic datasets that resemble training data. However, auditing their empirical privacy remains challen…