Zobrazeno 1 - 10
of 26 837
pro vyhledávání: '"Numeric, P."'
Autor:
Yu, Yijiong
Large Language Models (LLMs) have demonstrated remarkable capabilities in handling long texts and have almost perfect performance in traditional retrieval tasks. However, their performance significantly degrades when it comes to numerical calculation
Externí odkaz:
http://arxiv.org/abs/2411.10145
Autor:
Chen, Dillon Z., Thiébaux, Sylvie
Graph learning is naturally well suited for use in symbolic, object-centric planning due to its ability to exploit relational structures exhibited in planning domains and to take as input planning instances with arbitrary numbers of objects. Numeric
Externí odkaz:
http://arxiv.org/abs/2410.24080
A chessboard has the property that every row and every column has as many white squares as black squares. In this mostly methodological note, we address the problem of counting such rectangular arrays with a fixed (numeric) number of rows, but an arb
Externí odkaz:
http://arxiv.org/abs/2410.07435
Autor:
El-Shangiti, Ahmed Oumar, Hiraoka, Tatsuya, AlQuabeh, Hilal, Heinzerling, Benjamin, Inui, Kentaro
This paper investigates whether large language models (LLMs) utilize numerical attributes encoded in a low-dimensional subspace of the embedding space when answering logical comparison questions (e.g., Was Cristiano born before Messi?). We first iden
Externí odkaz:
http://arxiv.org/abs/2410.13194
Parser-based log compressors have been widely explored in recent years because the explosive growth of log volumes makes the compression performance of general-purpose compressors unsatisfactory. These parser-based compressors preprocess logs by grou
Externí odkaz:
http://arxiv.org/abs/2408.05760
Autor:
Huber, Christian, Waibel, Alexander
This paper addresses the problem of correctly formatting numeric expressions in automatic speech recognition (ASR) transcripts. This is challenging since the expected transcript format depends on the context, e.g., 1945 (year) vs. 19:45 (timestamp).
Externí odkaz:
http://arxiv.org/abs/2408.00004
In-context decision-making is an important capability of artificial general intelligence, which Large Language Models (LLMs) have effectively demonstrated in various scenarios. However, LLMs often face challenges when dealing with numerical contexts,
Externí odkaz:
http://arxiv.org/abs/2407.01887
Recently, many works have proposed various financial large language models (FinLLMs) by pre-training from scratch or fine-tuning open-sourced LLMs on financial corpora. However, existing FinLLMs exhibit unsatisfactory performance in understanding fin
Externí odkaz:
http://arxiv.org/abs/2405.00566
Autor:
Levina, Kristina, Pappas, Nikolaos, Karapantelakis, Athanasios, Feljan, Aneta Vulgarakis, Seipp, Jendrik
Reward machines inform reinforcement learning agents about the reward structure of the environment and often drastically speed up the learning process. However, reward machines only accept Boolean features such as robot-reached-gold. Consequently, ma
Externí odkaz:
http://arxiv.org/abs/2404.19370
Autor:
Chen, Dillon Z., Thiébaux, Sylvie
Heuristic search is a powerful approach for solving planning problems and numeric planning is no exception. In this paper, we boost the performance of heuristic search for numeric planning with various powerful techniques orthogonal to improving heur
Externí odkaz:
http://arxiv.org/abs/2404.05235