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Found 13 papers, 4 papers with code
Measuring Taiwanese Mandarin Language Understanding
We present TMLU, a holistic evaluation suit tailored for assessing the advanced knowledge and reasoning capability in LLMs, under the context of Taiwanese Mandarin.
Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model
Leveraging a comprehensive pretraining corpus and instruction-finetuning datasets, we have developed a model that not only understands the complexities of Traditional Chinese but also embodies the cultural context of Taiwan.
VoiceBank-2023: A Multi-Speaker Mandarin Speech Corpus for Constructing Personalized TTS Systems for the Speech Impaired
This paper reports the corpus design, corpus recording, data purging and correction for the corpus, and evaluations of the developed personalized TTS systems, for the VoiceBanking project.
LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models
We propose LLM-Eval, a unified multi-dimensional automatic evaluation method for open-domain conversations with large language models (LLMs).
Selective In-Context Data Augmentation for Intent Detection using Pointwise V-Information
This work focuses on in-context data augmentation for intent detection.
Ranked #1 on
Intent Detection
on BANKING77 10-shot
Knowledge-Grounded Conversational Data Augmentation with Generative Conversational Networks
Specifically, we show that for open-domain conversations with 10\% of seed data, our approach performs close to the baseline that uses 100% of the data, while for knowledge-grounded conversations, it achieves the same using only 1% of the data, on human ratings of engagingness, fluency, and relevance.
Miutsu: NTU's TaskBot for the Alexa Prize
This paper introduces Miutsu, National Taiwan University's Alexa Prize TaskBot, which is designed to assist users in completing tasks requiring multiple steps and decisions in two different domains -- home improvement and cooking.
SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues
The first one focuses on chatting with users and making them engage in the conversations, where selecting a proper topic to fit the dialogue context is essential for a successful dialogue.
Training Conversational Agents with Generative Conversational Networks
Rich, open-domain textual data available on the web resulted in great advancements for language processing.
Towards a Universal NLG for Dialogue Systems and Simulators with Future Bridging
In light of the recent success of data-driven approaches, we propose the novel future bridging NLG (FBNLG) concept for dialogue systems and simulators.
An Empirical Study of Cross-Lingual Transferability in Generative Dialogue State Tracker
There has been a rapid development in data-driven task-oriented dialogue systems with the benefit of large-scale datasets.
Angular clustering and host halo properties of [OII] emitters at $z >1$ in the Subaru HSC survey
From the constrained HOD model, the average mass of halos hosting the [OII] emitters is derived to be $\log{M_{eff}/(h^{-1}M_\odot)}=12. 70^{+0. 09}_{-0. 07}$ and $12. 61^{+0. 09}_{-0. 05}$ at z=1. 19 and 1. 47, respectively, which will become halos with the present-day mass, $M\sim 1. 5 \times 10^{13}h^{-1}M_\odot$.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics
A Power-Efficient Binary-Weight Spiking Neural Network Architecture for Real-Time Object Classification
Neural network hardware is considered an essential part of future edge devices.
