Zobrazeno 1 - 10
of 9 043
pro vyhledávání: '"Vardhan AS"'
Autor:
Khurdula, Harsha Vardhan, Rizk, Basem, Khaitan, Indus, Anjaria, Janit, Srivastava, Aviral, Khaitan, Rajvardhan
Current benchmarks for evaluating Vision Language Models (VLMs) often fall short in thoroughly assessing model abilities to understand and process complex visual and textual content. They typically focus on simple tasks that do not require deep reaso
Externí odkaz:
http://arxiv.org/abs/2411.15201
Neural networks trained with stochastic gradient descent exhibit an inductive bias towards simpler decision boundaries, typically converging to a narrow family of functions, and often fail to capture more complex features. This phenomenon raises conc
Externí odkaz:
http://arxiv.org/abs/2411.04569
The healthcare sector has experienced a rapid accumulation of digital data recently, especially in the form of electronic health records (EHRs). EHRs constitute a precious resource that IS researchers could utilize for clinical applications (e.g., mo
Externí odkaz:
http://arxiv.org/abs/2411.03224
Autor:
Dongre, Vardhan, Yang, Xiaocheng, Acikgoz, Emre Can, Dey, Suvodip, Tur, Gokhan, Hakkani-Tür, Dilek
Large language model (LLM)-based agents have been increasingly used to interact with external environments (e.g., games, APIs, etc.) and solve tasks. However, current frameworks do not enable these agents to work with users and interact with them to
Externí odkaz:
http://arxiv.org/abs/2411.00927
Publikováno v:
NeurIPS 2024 Workshop on Open-World Agents
Recent advancements in Large Language Model (LLM)-based frameworks have extended their capabilities to complex real-world applications, such as interactive web navigation. These systems, driven by user commands, navigate web browsers to complete task
Externí odkaz:
http://arxiv.org/abs/2410.23555
Publikováno v:
NeurIPS 2024 Workshop on Open-World Agents
Embodied agents designed to assist users with tasks must engage in natural language interactions, interpret instructions, execute actions, and communicate effectively to resolve issues. However, collecting large-scale, diverse datasets of situated hu
Externí odkaz:
http://arxiv.org/abs/2410.23535
Music source separation (MSS) is a task that involves isolating individual sound sources, or stems, from mixed audio signals. This paper presents an ensemble approach to MSS, combining several state-of-the-art architectures to achieve superior separa
Externí odkaz:
http://arxiv.org/abs/2410.20773
Many Bayesian statistical inference problems come down to computing a maximum a-posteriori (MAP) assignment of latent variables. Yet, standard methods for estimating the MAP assignment do not have a finite time guarantee that the algorithm has conver
Externí odkaz:
http://arxiv.org/abs/2410.19131
'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviews
The integrity of the peer-review process is vital for maintaining scientific rigor and trust within the academic community. With the steady increase in the usage of large language models (LLMs) like ChatGPT in academic writing, there is a growing con
Externí odkaz:
http://arxiv.org/abs/2410.09770
STImulated Raman Adiabatic Passage (STIRAP) is a powerful technique for robust state transfer capabilities in quantum systems. This method, however encounters challenges for its implementation as a gate in qubit-subspace due to its sensitivity to ini
Externí odkaz:
http://arxiv.org/abs/2410.04828