Zobrazeno 1 - 10
of 202 362
pro vyhledávání: '"Fail, P."'
While LLMs excel at multi-hop questions (e.g. "Who is the spouse of the performer of Imagine?") when using chain-of-thought reasoning (CoT), they struggle when forced to reason internally (without CoT). Previous work on the size and nature of this ga
Externí odkaz:
http://arxiv.org/abs/2411.16353
The application of transformer-based models on time series forecasting (TSF) tasks has long been popular to study. However, many of these works fail to beat the simple linear residual model, and the theoretical understanding of this issue is still li
Externí odkaz:
http://arxiv.org/abs/2412.06061
Human processing of idioms relies on understanding the contextual sentences in which idioms occur, as well as language-intrinsic features such as frequency and speaker-intrinsic factors like familiarity. While LLMs have shown high performance on idio
Externí odkaz:
http://arxiv.org/abs/2410.16069
We introduce Stereo Anywhere, a novel stereo-matching framework that combines geometric constraints with robust priors from monocular depth Vision Foundation Models (VFMs). By elegantly coupling these complementary worlds through a dual-branch archit
Externí odkaz:
http://arxiv.org/abs/2412.04472
Collaborative decision-making with artificial intelligence (AI) agents presents opportunities and challenges. While human-AI performance often surpasses that of individuals, the impact of such technology on human behavior remains insufficiently under
Externí odkaz:
http://arxiv.org/abs/2411.10176
Autor:
Diddee, Harshita, Ippolito, Daphne
Prior work has shown that language models can be tuned to follow user instructions using only a small set of high-quality instructions. This has accelerated the development of methods that filter a large, noisy instruction-tuning datasets down to hig
Externí odkaz:
http://arxiv.org/abs/2410.15225
Although LLMs are increasing the productivity of professional programmers, existing work shows that beginners struggle to prompt LLMs to solve text-to-code tasks. Why is this the case? This paper explores two competing hypotheses about the cause of s
Externí odkaz:
http://arxiv.org/abs/2410.19792
Deep learning methods - consisting of a class of deep neural networks (DNNs) trained by a stochastic gradient descent (SGD) optimization method - are nowadays key tools to solve data driven supervised learning problems. Despite the great success of S
Externí odkaz:
http://arxiv.org/abs/2410.10533
Autor:
Öncel, Fırat, Bethge, Matthias, Ermis, Beyza, Ravanelli, Mirco, Subakan, Cem, Yıldız, Çağatay
In the last decade, the generalization and adaptation abilities of deep learning models were typically evaluated on fixed training and test distributions. Contrary to traditional deep learning, large language models (LLMs) are (i) even more overparam
Externí odkaz:
http://arxiv.org/abs/2410.05581
Autor:
Liang, Chumeng, You, Jiaxuan
Membership inference attacks (MIAs) on diffusion models have emerged as potential evidence of unauthorized data usage in training pre-trained diffusion models. These attacks aim to detect the presence of specific images in training datasets of diffus
Externí odkaz:
http://arxiv.org/abs/2410.03640