Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Nouri, Elnaz"'
Autor:
Guan, Mingyu, Stokes, Jack W., Luo, Qinlong, Liu, Fuchen, Mehta, Purvanshi, Nouri, Elnaz, Kim, Taesoo
The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs) since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, existing methods ignore a tree hierarchy among met
Externí odkaz:
http://arxiv.org/abs/2402.13496
Autor:
Barke, Shraddha, Poelitz, Christian, Negreanu, Carina Suzana, Zorn, Benjamin, Cambronero, José, Gordon, Andrew D., Le, Vu, Nouri, Elnaz, Polikarpova, Nadia, Sarkar, Advait, Slininger, Brian, Toronto, Neil, Williams, Jack
Large language models (LLMs) are rapidly replacing help forums like StackOverflow, and are especially helpful for non-professional programmers and end users. These users are often interested in data-centric tasks, such as spreadsheet manipulation and
Externí odkaz:
http://arxiv.org/abs/2402.11734
Autor:
Singh, Mukul, Cambronero, José, Gulwani, Sumit, Le, Vu, Negreanu, Carina, Nouri, Elnaz, Raza, Mohammad, Verbruggen, Gust
Formatting is an important property in tables for visualization, presentation, and analysis. Spreadsheet software allows users to automatically format their tables by writing data-dependent conditional formatting (CF) rules. Writing such rules is oft
Externí odkaz:
http://arxiv.org/abs/2310.17306
Autor:
Payan, Justin, Mishra, Swaroop, Singh, Mukul, Negreanu, Carina, Poelitz, Christian, Baral, Chitta, Roy, Subhro, Chakravarthy, Rasika, Van Durme, Benjamin, Nouri, Elnaz
With the evolution of Large Language Models (LLMs) we can solve increasingly more complex NLP tasks across various domains, including spreadsheets. This work investigates whether LLMs can generate code (Excel OfficeScripts, a TypeScript API for execu
Externí odkaz:
http://arxiv.org/abs/2310.14495
The success of graph neural networks on graph-based web mining highly relies on abundant human-annotated data, which is laborious to obtain in practice. When only few labeled nodes are available, how to improve their robustness is a key to achieve re
Externí odkaz:
http://arxiv.org/abs/2208.12422
Autor:
Mishra, Swaroop, Nouri, Elnaz
Controlling the text generated by language models and customizing the content has been a long-standing challenge. Existing prompting techniques proposed in pursuit of providing control are task-specific and lack generality; this provides overwhelming
Externí odkaz:
http://arxiv.org/abs/2208.08232
Autor:
Peng, Baolin, Galley, Michel, He, Pengcheng, Brockett, Chris, Liden, Lars, Nouri, Elnaz, Yu, Zhou, Dolan, Bill, Gao, Jianfeng
We introduce GODEL (Grounded Open Dialogue Language Model), a large pre-trained language model for dialog. In contrast with earlier models such as DialoGPT, GODEL leverages a new phase of grounded pre-training designed to better support adapting GODE
Externí odkaz:
http://arxiv.org/abs/2206.11309
While digital assistants are increasingly used to help with various productivity tasks, less attention has been paid to employing them in the domain of business documents. To build an agent that can handle users' information needs in this domain, we
Externí odkaz:
http://arxiv.org/abs/2203.15073
As large Pre-trained Language Models (PLMs) trained on large amounts of data in an unsupervised manner become more ubiquitous, identifying various types of bias in the text has come into sharp focus. Existing "Stereotype Detection" datasets mainly ad
Externí odkaz:
http://arxiv.org/abs/2203.14349
Autor:
Arumugam, Dilip, Dey, Debadeepta, Agarwal, Alekh, Celikyilmaz, Asli, Nouri, Elnaz, Dolan, Bill
While recent state-of-the-art results for adversarial imitation-learning algorithms are encouraging, recent works exploring the imitation learning from observation (ILO) setting, where trajectories \textit{only} contain expert observations, have not
Externí odkaz:
http://arxiv.org/abs/2006.10810