Search Results for author:
Found 10 papers, 3 papers with code
Familia: An Open-Source Toolkit for Industrial Topic Modeling
Familia is an open-source toolkit for pragmatic topic modeling in industry.
Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering
In order to relieve burdens of software engineers without knowledge of Bayesian networks, Familia is able to conduct automatic parameter inference for a variety of topic models.
Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning
Our findings elucidate that our proposed methodology establishes a new benchmark for SOTA performance in food recognition on the CNFOOD-241 dataset.
Ranked #1 on
Fine-Grained Image Recognition
on CNFOOD-241-Chen
Latent Topic Embedding
Topic modeling and word embedding are two important techniques for deriving latent semantics from data.
DAL: Dual Adversarial Learning for Dialogue Generation
DAL is the first work to innovatively utilizes the duality between query generation and response generation to avoid safe responses and increase the diversity of the generated responses.
L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition
Modern Automatic Speech Recognition (ASR) systems primarily rely on scores from an Acoustic Model (AM) and a Language Model (LM) to rescore the N-best lists.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Chameleon: A Language Model Adaptation Toolkit for Automatic Speech Recognition of Conversational Speech
With this demonstration, the audience can experience the effect of LMA in an interactive and real-time fashion.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Question
We first identify a new task named Speech-to-SQL, which aims to understand the information conveyed by human speech and directly translate it into structured query language (SQL) statements.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Learn to Cluster Faces with Better Subgraphs
Face clustering can provide pseudo-labels to the massive unlabeled face data and improve the performance of different face recognition models.
A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models
The springing up of Large Language Models (LLMs) has shifted the community from single-task-orientated natural language processing (NLP) research to a holistic end-to-end multi-task learning paradigm.
