Search Results for author:
Found 16 papers, 4 papers with code
Does Mapo Tofu Contain Coffee? Probing LLMs for Food-related Cultural Knowledge
Recent studies have highlighted the presence of cultural biases in Large Language Models (LLMs), yet often lack a robust methodology to dissect these phenomena comprehensively.
Exploring Visual Culture Awareness in GPT-4V: A Comprehensive Probing
Pretrained large Vision-Language models have drawn considerable interest in recent years due to their remarkable performance.
Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys
The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory.
MLPs Compass: What is learned when MLPs are combined with PLMs?
While Transformer-based pre-trained language models and their variants exhibit strong semantic representation capabilities, the question of comprehending the information gain derived from the additional components of PLMs remains an open question in this field.
Cultural Adaptation of Recipes
We introduce a new task involving the translation and cultural adaptation of recipes between Chinese and English-speaking cuisines.
Geo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking
Chinese geographic re-ranking task aims to find the most relevant addresses among retrieved candidates, which is crucial for location-related services such as navigation maps.
Pay More Attention to Relation Exploration for Knowledge Base Question Answering
In this study, we propose a novel framework, RE-KBQA, that utilizes relations in the knowledge base to enhance entity representation and introduce additional supervision.
Cross-Cultural Transfer Learning for Chinese Offensive Language Detection
Detecting offensive language is a challenging task.
Cultural Vocal Bursts Intensity Prediction
Few-Shot Learning
+1
Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study
The recent release of ChatGPT has garnered widespread recognition for its exceptional ability to generate human-like responses in dialogue.
Deep-Learning Tool for Early Identifying Non-Traumatic Intracranial Hemorrhage Etiology based on CT Scan
Conclusions: The proposed deep learning algorithms can be an effective tool for early identification of hemorrhage etiologies based on NCCT scans.
Explore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation
Sign language recognition and translation first uses a recognition module to generate glosses from sign language videos and then employs a translation module to translate glosses into spoken sentences.
Spiral Language Modeling
In almost all text generation applications, word sequences are constructed in a left-to-right (L2R) or right-to-left (R2L) manner, as natural language sentences are written either L2R or R2L.
Deep Active Learning for Remote Sensing Object Detection
Recently, CNN object detectors have achieved high accuracy on remote sensing images but require huge labor and time costs on annotation.
Understanding Semantics from Speech Through Pre-training
End-to-end Spoken Language Understanding (SLU) is proposed to infer the semantic meaning directly from audio features without intermediate text representation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Learning-to-Ask: Knowledge Acquisition via 20 Questions
Almost all the knowledge empowered applications rely upon accurate knowledge, which has to be either collected manually with high cost, or extracted automatically with unignorable errors.
