Zobrazeno 1 - 10
of 3 357
pro vyhledávání: '"Duc, Anh"'
Autor:
Nguyen, Quang Duc, Nguyen, Tung, Nguyen, Duc Anh, Van, Linh Ngo, Dinh, Sang, Nguyen, Thien Huu
Uncovering hidden topics from short texts is challenging for traditional and neural models due to data sparsity, which limits word co-occurrence patterns, and label sparsity, stemming from incomplete reconstruction targets. Although data aggregation
Externí odkaz:
http://arxiv.org/abs/2412.00525
Autor:
Vu, Duc Anh, Duy, Nguyen Tran Cong, Wu, Xiaobao, Nhat, Hoang Minh, Mingzhe, Du, Thong, Nguyen Thanh, Luu, Anh Tuan
Large Language Models (LLMs) have shown strong in-context learning (ICL) abilities with a few demonstrations. However, one critical challenge is how to select demonstrations to elicit the full potential of LLMs. In this paper, we propose Curriculum D
Externí odkaz:
http://arxiv.org/abs/2411.18126
Fairness in artificial intelligence and machine learning (AI/ML) models is becoming critically important, especially as decisions made by these systems impact diverse groups. In education, a vital sector for all countries, the widespread application
Externí odkaz:
http://arxiv.org/abs/2410.06423
Autor:
Pham, Duy-Tung, Vu, Thien Trang Nguyen, Nguyen, Tung, Van, Linh Ngo, Nguyen, Duc Anh, Nguyen, Thien Huu
Recent advances in neural topic models have concentrated on two primary directions: the integration of the inference network (encoder) with a pre-trained language model (PLM) and the modeling of the relationship between words and topics in the genera
Externí odkaz:
http://arxiv.org/abs/2409.19749
Time series data from various domains is continuously growing, and extracting and analyzing temporal patterns within these series can provide valuable insights. Temporal pattern mining (TPM) extends traditional pattern mining by incorporating event t
Externí odkaz:
http://arxiv.org/abs/2409.05042
Large Language Models (LLMs) have recently advanced many applications on software engineering tasks, particularly the potential for code generation. Among contemporary challenges, code generated by LLMs often suffers from inaccuracies and hallucinati
Externí odkaz:
http://arxiv.org/abs/2408.15658
COVID 19 pandemic has disrupted the global market and workplace landscape. As a response, hybrid work situations have become popular in the software business sector. This way of working has an impact on software companies. This study investigates sof
Externí odkaz:
http://arxiv.org/abs/2407.14857
The proliferation of online toxic speech is a pertinent problem posing threats to demographic groups. While explicit toxic speech contains offensive lexical signals, implicit one consists of coded or indirect language. Therefore, it is crucial for mo
Externí odkaz:
http://arxiv.org/abs/2403.16685
Stack Overflow is a prominent Q and A forum, supporting developers in seeking suitable resources on programming-related matters. Having high-quality question titles is an effective means to attract developers' attention. Unfortunately, this is often
Externí odkaz:
http://arxiv.org/abs/2406.15633
Autor:
Trinh, Duc-Anh, V., Adwaith K., Branco, Mickael, Rouxel, Aliénor, Welinski, Sacha, Berger, Perrine, Goldfarb, Fabienne, Bretenaker, Fabien
Publikováno v:
Applied Physics Letters 125, 154001 (2024)
We propose and demonstrate a modulation transfer protocol to increase the detection sensitivity of a Rydberg RF receiver to fields out of resonance from the transition between Rydberg levels. This protocol is based on a phase modulation of the contro
Externí odkaz:
http://arxiv.org/abs/2405.03618