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The presentation of results from Systematic Literature Reviews (SLRs) is generally done using tables. Prior research suggests that results summarized in tables are often difficult for readers to understand. One alternative to improve…
Scene graphs (SGs) represent objects and their relationships as structured graphs, enabling applications in image generation, robotics, and 3D understanding. Recent work suggests that conditioning image generation on scene graphs improves…
Recent works show that interactive documents connecting text with visualizations facilitate reading comprehension. However, creating this type of content requires specialized knowledge. We present ChartText, a method that links text with…
Ever growing number of image documents available on the Internet continuously motivates research in better annotation models and more efficient retrieval methods. Formal knowledge representation of objects and events in pictures, their…
Accurate interpretation and visual representation of complex prompts involving multiple objects, attributes, and spatial relationships is a critical challenge in text-to-image synthesis. Despite recent advancements in generating…
Compositional speech-to-speech translation (S2ST) systems built upon speech large language models (SpeechLLMs) have recently shown promising performance. However, existing S2ST systems often either neglect source-language information or…
Diagrams are essential tools for problem-solving and communication as they externalize conceptual structures using spatial relationships. But when picking a diagramming framework, users are faced with a dilemma. They can either use a highly…
Formality is one of the important characteristics of text documents. The automatic detection of the formality level of a text is potentially beneficial for various natural language processing tasks. Before, two large-scale datasets were…
Given a pair of source and reference speech recordings, speech-to-speech (S2S) emotion style transfer involves the generation of an output speech that mimics the emotion characteristics of the reference while preserving the content and…
Flow 2.0 is an end-to-end easy-of-use software that allows us to quickly, robustly and accurately perform a batch process real-time phase contrast data and multivariate analysis of the effect of respiration on cerebral fluids circulation.…
Scene flow estimation is a foundational task for many robotic applications, including robust dynamic object detection, automatic labeling, and sensor synchronization. Two types of approaches to the problem have evolved: 1) Supervised and 2)…
Text-guided molecule generation is a task where molecules are generated to match specific textual descriptions. Recently, most existing SMILES-based molecule generation methods rely on an autoregressive architecture. In this work, we…
Emotion Classification based on text is a task with many applications which has received growing interest in recent years. This paper presents a preliminary study with the goal to help researchers and practitioners gain insight into…
Scene text recognition (STR) suffers from challenges of either less realistic synthetic training data or the difficulty of collecting sufficient high-quality real-world data, limiting the effectiveness of trained models. Meanwhile, despite…
This paper presents a software platform, named BiNS2, able to simulate diffusion-based molecular communications with drift inside blood vessels. The contribution of the paper is twofold. First a detailed description of the simulator is…
We present a light formalism for proofs that encodes their inferential structure, along with a system that transforms these representations into flow-chart diagrams. Such diagrams should improve the comprehensibility of proofs. We discuss…
The advantage of having a high-fidelity instrument simulation tool developed in tandem with novel instrumentation is having the ability to investigate, in isolation and in combination, the wide parameter space set by the instrument design.…
As a novel contribution to the problem of semantifying biological assays, in this paper, we propose a neural-network-based approach to automatically semantify, thereby structure, unstructured bioassay text descriptions. Experimental…
Biomedical research is intensive in processing information in the previously published papers. This motivated a lot of efforts to provide tools for text mining and information extraction from PDF documents over the past decade. The *nix…
Despite rapid advances in the field of emotional text-to-speech (TTS), recent studies primarily focus on mimicking the average style of a particular emotion. As a result, the ability to manipulate speech emotion remains constrained to…