Zobrazeno 1 - 10
of 24 744
pro vyhledávání: '"Ameen, A."'
Large language models (LLMs) have demonstrated impressive few-shot in-context learning (ICL) abilities. Still, we show that they are sometimes prone to a `copying bias', where they copy answers from provided examples instead of learning the underlyin
Externí odkaz:
http://arxiv.org/abs/2410.01288
Autor:
Abdulla, Hemin Sardar, Ameen, Azad A., Saeed, Sarwar Ibrahim, Mohammed, Ismail Asaad, Rashid, Tarik A.
The rapid advancement of intelligent technology has led to the development of optimization algorithms that leverage natural behaviors to address complex issues. Among these, the Rat Swarm Optimizer (RSO), inspired by rats' social and behavioral chara
Externí odkaz:
http://arxiv.org/abs/2410.03684
Autor:
Ameen, Salem, Vokhidov, Husan F.
This paper presents a study on autonomous robot navigation, focusing on three key behaviors: Odometry, Target Tracking, and Obstacle Avoidance. Each behavior is described in detail, along with experimental setups for simulated and real-world environm
Externí odkaz:
http://arxiv.org/abs/2407.06118
Autor:
Adediran, Enoch, Ameen, Salem
As the pace of AI technology continues to accelerate, more tools have become available to researchers to solve longstanding problems, Hybrid approaches available today continue to push the computational limits of efficiency and precision. One of such
Externí odkaz:
http://arxiv.org/abs/2406.13064
In the intricate field of medical diagnostics, capturing the subtle manifestations of diseases remains a challenge. Traditional methods, often binary in nature, may not encapsulate the nuanced variances that exist in real-world clinical scenarios. Th
Externí odkaz:
http://arxiv.org/abs/2406.13015
Autor:
Parthasarathy, Ambreesh, Phalnikar, Aditya, Krishnan, Gokul S, Jauhar, Ameen, Ravindran, Balaraman
This paper forms the second of a two-part series on the value of a participatory approach to AI development and deployment. The first paper had crafted a principled, as well as pragmatic, justification for deploying participatory methods in these two
Externí odkaz:
http://arxiv.org/abs/2407.13103
Autor:
Parthasarathy, Ambreesh, Phalnikar, Aditya, Jauhar, Ameen, Somayajula, Dhruv, Krishnan, Gokul S, Ravindran, Balaraman
The widespread adoption of Artificial Intelligence (AI) technologies in the public and private sectors has resulted in them significantly impacting the lives of people in new and unexpected ways. In this context, it becomes important to inquire how t
Externí odkaz:
http://arxiv.org/abs/2407.13100
Recent advances in efficient sequence modeling have led to attention-free layers, such as Mamba, RWKV, and various gated RNNs, all featuring sub-quadratic complexity in sequence length and excellent scaling properties, enabling the construction of a
Externí odkaz:
http://arxiv.org/abs/2405.16504
Detecting out-of-distribution (OOD) instances is crucial for the reliable deployment of machine learning models in real-world scenarios. OOD inputs are commonly expected to cause a more uncertain prediction in the primary task; however, there are OOD
Externí odkaz:
http://arxiv.org/abs/2405.12658
Autor:
Ameen, Taha, Hajek, Bruce
This work studies fundamental limits for recovering the underlying correspondence among multiple correlated random graphs. We identify a necessary condition for any algorithm to correctly match all nodes across all graphs, and propose two algorithms
Externí odkaz:
http://arxiv.org/abs/2405.12293