A Supervised learning for the identification of semantic relations in parallel enumerative structures (Apprentissage supervis\'e pour l'identification de relations s\'emantiques au sein de structures \'enum\'eratives parall\`eles) [in French]
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Guiding Enumerative Program Synthesis with Large Language Models
Pre-trained Large Language Models (LLMs) are beginning to dominate the discourse around automatic code generation with natural language specifications. In contrast, the best-performing synthesizers in the domain of forma…
Code GenerationProgram SynthesisTemporal Properties of Enumerative Shaping: Autocorrelation and Energy Dispersion Index
We study the effective SNR behavior of various enumerative amplitude shaping algorithms. We show that their relative behavior can be explained via the temporal autocorrelation function or via the energy dispersion index.
A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching
We present a latent variable model for predicting the relationship between a pair of text sequences. Unlike previous auto-encoding--based approaches that consider each sequence separately, our proposed framework utilizes…
DecoderNatural Language InferenceParaphrase IdentificationSentenceAutomatic Identification of AltLexes using Monolingual Parallel Corpora
The automatic identification of discourse relations is still a challenging task in natural language processing. Discourse connectives, such as "since" or "but", are the most informative cues to identify explicit relation…
Text SimplificationScaling Neural Program Synthesis with Distribution-based Search
We consider the problem of automatically constructing computer programs from input-output examples. We investigate how to augment probabilistic and neural program synthesis methods with new search algorithms, proposing a…
Program Synthesis