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Found 12 papers, 1 papers with code
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs
Large language models (LLMs) demonstrate strong reasoning abilities when prompted to generate chain-of-thought (CoT) explanations alongside answers.
Simultaneous Machine Translation with Large Language Models
The results show that LLM outperforms dedicated MT models in terms of BLEU and LAAL metrics.
Language Independent Neuro-Symbolic Semantic Parsing for Form Understanding
Our model parses a form into a word-relation graph in order to identify entities and relations jointly and reduce the time complexity of inference.
Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain
In order to exploit the potentially useful and rich information from such sources, it is necessary to extract not only the relevant entities and concepts but also their semantic relations, together with the uncertainty associated with the extracted knowledge (i. e., in the form of probabilistic knowledge graphs).
Few-shot Domain-Adaptive Visually-fused Event Detection from Text
In this paper, we present a novel domain-adaptive visually-fused event detection approach that can be trained on a few labelled image-text paired data points.
On Robustness of Prompt-based Semantic Parsing with Large Pre-trained Language Model: An Empirical Study on Codex
Semantic parsing is a technique aimed at constructing a structured representation of the meaning of a natural-language question.
Adaptive Population-based Simulated Annealing for Uncertain Resource Constrained Job Scheduling
While a number of optimisation methods have been proposed to tackle the deterministic problem, the uncertainty associated with resource availability, an inevitable challenge in mining operations, has received less attention.
Paraphrasing Techniques for Maritime QA system
In this paper, we investigate how to exploit paraphrasing methods for the automated generation of large-scale training datasets (in the form of paraphrased utterances and their corresponding logical forms in SQL format) and present our experimental results using real-world data in the maritime domain.
Recovering Faces from Portraits with Auxiliary Facial Attributes
%Our method can recover high-quality photorealistic faces from unaligned portraits while preserving the identity of the face images as well as it can reconstruct a photorealistic face image with a desired set of attributes.
Identity-preserving Face Recovery from Stylized Portraits
We develop an Identity-preserving Face Recovery from Portraits (IFRP) method that utilizes a Style Removal network (SRN) and a Discriminative Network (DN).
Face Destylization
To enforce the destylized faces to be similar to authentic face images, we employ a discriminative network, which consists of convolutional and fully connected layers.
Identity-preserving Face Recovery from Portraits
In this paper, we present a new Identity-preserving Face Recovery from Portraits (IFRP) to recover latent photorealistic faces from unaligned stylized portraits.
