Zobrazeno 1 - 10
of 12 839
pro vyhledávání: '"A. Saket"'
Autor:
Bentert, Matthias, Fomin, Fedor V., Golovach, Petr A., Korhonen, Tuukka, Lochet, William, Panolan, Fahad, Ramanujan, M. S., Saurabh, Saket, Simonov, Kirill
Cycle packing is a fundamental problem in optimization, graph theory, and algorithms. Motivated by recent advancements in finding vertex-disjoint paths between a specified set of vertices that either minimize the total length of the paths [Bj\"orklun
Externí odkaz:
http://arxiv.org/abs/2410.18878
In the Hedge Cut problem, the edges of a graph are partitioned into groups called hedges, and the question is what is the minimum number of hedges to delete to disconnect the graph. Ghaffari, Karger, and Panigrahi [SODA 2017] showed that Hedge Cut ca
Externí odkaz:
http://arxiv.org/abs/2410.17641
Historically, machine learning training pipelines have predominantly relied on batch training models, retraining models every few hours. However, industrial practitioners have proved that real-time training can lead to a more adaptive and personalize
Externí odkaz:
http://arxiv.org/abs/2410.15533
The rise in popularity of social media platforms, has resulted in millions of new, content pieces being created every day. This surge in content creation underscores the need to pay attention to our design choices as they can greatly impact how long
Externí odkaz:
http://arxiv.org/abs/2410.15174
Autor:
Ko, Jongwoo, Dingliwal, Saket, Ganesh, Bhavana, Sengupta, Sailik, Bodapati, Sravan, Galstyan, Aram
Direct alignment algorithms (DAAs), such as direct preference optimization (DPO), have become popular alternatives for Reinforcement Learning from Human Feedback (RLHF) due to their simplicity, efficiency, and stability. However, the preferences used
Externí odkaz:
http://arxiv.org/abs/2410.09362
Autor:
Singh, Aditi, Ehtesham, Abul, Gupta, Gaurav Kumar, Chatta, Nikhil Kumar, Kumar, Saket, Khoei, Tala Talaei
In this paper, we conduct a comprehensive SWOT analysis of prompt engineering techniques within the realm of Large Language Models (LLMs). Emphasizing linguistic principles, we examine various techniques to identify their strengths, weaknesses, oppor
Externí odkaz:
http://arxiv.org/abs/2410.12843
Large language models (LLMs) can generate fluent summaries across domains using prompting techniques, reducing the need to train models for summarization applications. However, crafting effective prompts that guide LLMs to generate summaries with the
Externí odkaz:
http://arxiv.org/abs/2410.02741
We give two new approximation algorithms to compute the fractional hypertree width of an input hypergraph. The first algorithm takes as input $n$-vertex $m$-edge hypergraph $H$ of fractional hypertree width at most $\omega$, runs in polynomial time a
Externí odkaz:
http://arxiv.org/abs/2409.20172
For a finite set $\mathcal{F}$ of graphs, the $\mathcal{F}$-Hitting problem aims to compute, for a given graph $G$ (taken from some graph class $\mathcal{G}$) of $n$ vertices (and $m$ edges) and a parameter $k\in\mathbb{N}$, a set $S$ of vertices in
Externí odkaz:
http://arxiv.org/abs/2409.04786
This paper explores the potential of using Large Language Models (LLMs) to automate the evaluation of responses in medical Question and Answer (Q\&A) systems, a crucial form of Natural Language Processing. Traditionally, human evaluation has been ind
Externí odkaz:
http://arxiv.org/abs/2409.01941