116 citations · 170 across the 6 of their papers we have counts for
6 papers
Audio-Language Models for Audio-Centric Tasks: A Systematic Survey
Yi Su, Jisheng Bai, Qisheng Xu +2
Audio-Language Models (ALMs), trained on paired audio-text data, are designed to process, understand, and reason about audio-centric multimodal content. Unlike traditional supervis…
KGLens: Towards Efficient and Effective Knowledge Probing of Large Language Models with Knowledge Graphs
Shangshang Zheng, He Bai, Yizhe Zhang +3
Large Language Models (LLMs) might hallucinate facts, while curated Knowledge Graph (KGs) are typically factually reliable especially with domain-specific knowledge. Measuring the…
Leveraging Large Language Models for Exploiting ASR Uncertainty
Pranay Dighe, Yi Su, Shangshang Zheng +4
While large language models excel in a variety of natural language processing (NLP) tasks, to perform well on spoken language understanding (SLU) tasks, they must either rely on of…
Tianshou: a Highly Modularized Deep Reinforcement Learning Library
Jiayi Weng, Huayu Chen, Dong Yan +6
In this paper, we present Tianshou, a highly modularized Python library for deep reinforcement learning (DRL) that uses PyTorch as its backend. Tianshou intends to be research-frie…
R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling
Xiang Hu, Haitao Mi, Zujie Wen +4
Human language understanding operates at multiple levels of granularity (e.g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combi…
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
Jianfeng Gao, Qiang Wu, Chris Burges +5
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The resu…