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20212026
most citedEconomic Recession Prediction Using Deep Neural Network

4 citations · 8 across the 10 of their papers we have counts for

collaborators

10 papers

cs.SD2026

Unlocking Large Audio-Language Models for Interactive Language Learning

Hongfu Liu, Zhouying Cui, Xiangming Gu +1

Achieving pronunciation proficiency in a second language (L2) remains a challenge, despite the development of Computer-Assisted Pronunciation Training (CAPT) systems. Traditional C…

cs.CV2025

Fostering Video Reasoning via Next-Event Prediction

Haonan Wang, Hongfu Liu, Xiangyan Liu +4

Next-token prediction serves as the foundational learning task enabling reasoning in LLMs. But what should the learning task be when aiming to equip MLLMs with temporal reasoning c…

cs.CR2024★ 1 cited

On Calibration of LLM-based Guard Models for Reliable Content Moderation

Hongfu Liu, Hengguan Huang, Xiangming Gu +2

Large language models (LLMs) pose significant risks due to the potential for generating harmful content or users attempting to evade guardrails. Existing studies have developed LLM…

cs.CL2024★ 1 cited

Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models

Hongfu Liu, Yuxi Xie, Ye Wang +1

Language Language Models (LLMs) face safety concerns due to potential misuse by malicious users. Recent red-teaming efforts have identified adversarial suffixes capable of jailbrea…

cs.CL2024

Benchmarking Large Language Models on Communicative Medical Coaching: a Novel System and Dataset

Hengguan Huang, Songtao Wang, Hongfu Liu +2

Traditional applications of natural language processing (NLP) in healthcare have predominantly focused on patient-centered services, enhancing patient interactions and care deliver…

cs.CL2023★ 1 cited

Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning

Hongfu Liu, Ye Wang

Large Language models (LLMs) possess the capability to engage In-context Learning (ICL) by leveraging a few demonstrations pertaining to a new downstream task as conditions. Howeve…

cs.SD2023

Advancing Test-Time Adaptation in Wild Acoustic Test Settings

Hongfu Liu, Hengguan Huang, Ye Wang

Acoustic foundation models, fine-tuned for Automatic Speech Recognition (ASR), suffer from performance degradation in wild acoustic test settings when deployed in real-world scenar…

cs.SD2023

Zero-Shot Automatic Pronunciation Assessment

Hongfu Liu, Mingqian Shi, Ye Wang

Automatic Pronunciation Assessment (APA) is vital for computer-assisted language learning. Prior methods rely on annotated speech-text data to train Automatic Speech Recognition (A…

econ.GN2021★ 4 cited

Economic Recession Prediction Using Deep Neural Network

Zihao Wang, Kun Li, Steve Q. Xia +1

We investigate the effectiveness of different machine learning methodologies in predicting economic cycles. We identify the deep learning methodology of Bi-LSTM with Autoencoder as…

cs.LG2021★ 1 cited

STRODE: Stochastic Boundary Ordinary Differential Equation

Hengguan Huang, Hongfu Liu, Hao Wang +2

Perception of time from sequentially acquired sensory inputs is rooted in everyday behaviors of individual organisms. Yet, most algorithms for time-series modeling fail to learn dy…