A5101540966- Natural Language Processing Techniques
- Topic Modeling
- Multimodal Machine Learning Applications
- Advanced Data Compression Techniques
- EFL/ESL Teaching and Learning
- Educational and Psychological Assessments
- Text and Document Classification Technologies
- Speech Recognition and Synthesis
- Innovative Education and Learning Practices
- Speech and Audio Processing
- Multilingual Education and Policy
- Educator Training and Historical Pedagogy
Google (United Kingdom)
2023
Pretrained language models such as BERT have been shown to be exceptionally effective for text ranking. However, there are limited studies on how leverage more powerful sequence-to-sequence T5. Existing attempts usually formulate ranking a classification problem and rely postprocessing obtain ranked list. In this paper, we propose RankT5 study two T5-based model structures, an encoder-decoder encoder-only one, so that they not only can directly output scores each query-document pair, but...
We report on the results of first evaluations for BBN/LIMSI system under new DARPA EARS program. The were carried out conversational telephone speech (CTS) and broadcast news (BN) three languages: English, Mandarin, Arabic. In addition to providing descriptions evaluation results, paper highlights methods that worked well across two domains those few one domain but not other. For BN evaluations, which had be run 10 times real-time, we demonstrated a joint with time constraint achieved better...
Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and approach unseen objects in unfamiliar environments has emerged as a particularly challenging task within the domain of Embodied AI. Existing datasets for developing ZSON algorithms lack consideration dynamic obstacles, object attribute diversity, scene texts, thus exhibiting noticeable discrepancies from real-world situations. To address these issues, we propose Dataset Open-Vocabulary Dynamic Environments (DOZE)...
Abstract The availability of large, high-quality datasets has been a major driver recent progress in question answering (QA). Such annotated datasets, however, are difficult and costly to collect, rarely exist languages other than English, rendering QA technology inaccessible underrepresented languages. An alternative building large monolingual training is leverage pre-trained language models (PLMs) under few-shot learning setting. Our approach, QAmeleon, uses PLM automatically generate...