Zobrazeno 1 - 10
of 5 858
pro vyhledávání: '"Leonardo, F."'
Augmenting Large Language Models (LLMs) with information retrieval capabilities (i.e., Retrieval-Augmented Generation (RAG)) has proven beneficial for knowledge-intensive tasks. However, understanding users' contextual search intent when generating r
Externí odkaz:
http://arxiv.org/abs/2409.15515
Autor:
Cho, Hyundong, Jedema, Nicolaas, Ribeiro, Leonardo F. R., Sharma, Karishma, Szekely, Pedro, Moschitti, Alessandro, Janssen, Ruben, May, Jonathan
Current instruction-tuned language models are exclusively trained with textual preference data and thus are often not aligned with the unique requirements of other modalities, such as speech. To better align language models with the speech domain, we
Externí odkaz:
http://arxiv.org/abs/2409.14672
Autor:
Wang, Zhuoer, Ribeiro, Leonardo F. R., Papangelis, Alexandros, Mukherjee, Rohan, Wang, Tzu-Yen, Zhao, Xinyan, Biswas, Arijit, Caverlee, James, Metallinou, Angeliki
API call generation is the cornerstone of large language models' tool-using ability that provides access to the larger world. However, existing supervised and in-context learning approaches suffer from high training costs, poor data efficiency, and g
Externí odkaz:
http://arxiv.org/abs/2407.13945
Representation learning is a powerful tool that enables learning over large multitudes of agents or domains by enforcing that all agents operate on a shared set of learned features. However, many robotics or controls applications that would benefit f
Externí odkaz:
http://arxiv.org/abs/2407.05781
We address the problem of designing an LQR controller in a distributed setting, where M similar but not identical systems share their locally computed policy gradient (PG) estimates with a server that aggregates the estimates and computes a controlle
Externí odkaz:
http://arxiv.org/abs/2404.09061
Autor:
Gabburo, Matteo, Jedema, Nicolaas Paul, Garg, Siddhant, Ribeiro, Leonardo F. R., Moschitti, Alessandro
In this paper, we investigate which questions are challenging for retrieval-based Question Answering (QA). We (i) propose retrieval complexity (RC), a novel metric conditioned on the completeness of retrieved documents, which measures the difficulty
Externí odkaz:
http://arxiv.org/abs/2406.03592
In arXiv:2404.19088, we initiated a program linking birational invariants with smooth ones and offering new interpretations of classical invariants, such as the Kervaire-Milnor invariants. Here, we rely on the profound geometric reasoning provided by
Externí odkaz:
http://arxiv.org/abs/2405.07322
Autor:
Nawrath, Marcel, Nowak, Agnieszka, Ratz, Tristan, Walenta, Danilo C., Opitz, Juri, Ribeiro, Leonardo F. R., Sedoc, João, Deutsch, Daniel, Mille, Simon, Liu, Yixin, Zhang, Lining, Gehrmann, Sebastian, Mahamood, Saad, Clinciu, Miruna, Chandu, Khyathi, Hou, Yufang
At the heart of the Pyramid evaluation method for text summarization lie human written summary content units (SCUs). These SCUs are concise sentences that decompose a summary into small facts. Such SCUs can be used to judge the quality of a candidate
Externí odkaz:
http://arxiv.org/abs/2404.01701
Autor:
Cavenaghi, Leonardo F., Grama, Lino
Since the advent of new pairwise non-diffeomorphic structures on smooth manifolds, it has been questioned whether two topologically identical manifolds could admit different geometries. Not surprisingly, physicists have wondered whether a smooth stru
Externí odkaz:
http://arxiv.org/abs/2403.08960
Autor:
Calderón, Leonardo F., Brumer, Paul
The interplay between electronic and intramolecular high-frequency vibrational degrees of freedom is ubiquitous in natural light-harvesting systems. Recent studies have indicated that an intramolecular vibrational donor-acceptor frequency difference
Externí odkaz:
http://arxiv.org/abs/2402.16881