The Utility of "Even if..." Semifactual Explanation to Optimise Positive Outcomes

When users receive either a positive or negative outcome from an automated system, Explainable AI (XAI) has almost exclusively focused on how to mutate negative outcomes into positive ones by crossing a decision boundary using counterfactuals (e.g., \textit{"If you earn 2k more, we will accept your loan application"}). Here, we instead focus on \textit{positive} outcomes, and take the novel step of using XAI to optimise them (e.g., \textit{"Even if you wish to half your down-payment, we will still accept your loan application"}). Explanations such as these that employ "even if..." reasoning, and do not cross a decision boundary, are known as semifactuals. To instantiate semifactuals in this context, we introduce the concept of \textit{Gain} (i.e., how much a user stands to benefit from the explanation), and consider the first causal formalisation of semifactuals. Tests on benchmark datasets show our algorithms are better at maximising gain compared to prior work, and that causality is important in the process. Most importantly however, a user study supports our main hypothesis by showing people find semifactual explanations more useful than counterfactuals when they receive the positive outcome of a loan acceptance

DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues

Interpersonal language style shifting in dialogues is an interesting and almost instinctive ability of human. Understanding interpersonal relationship from language content is also a crucial step toward further understanding dialogues. Previous work mainly focuses on relation extraction between named entities in texts. In this paper, we propose the task of relation classification of interlocutors based on their dialogues. We crawled movie scripts from IMSDb, and annotated the relation labels for each session according to 13 pre-defined relationships. The annotated dataset DDRel consists of 6300 dyadic dialogue sessions between 694 pair of speakers with 53,126 utterances in total. We also construct session-level and pair-level relation classification tasks with widely-accepted baselines. The experimental results show that this task is challenging for existing models and the dataset will be useful for future research.Comment: This paper has been accepted by AAAI202

Automated Whiteboard Eraser

The Automated Whiteboard Eraser is a product designed to erase whiteboards with the touch of a button. With this product students and teachers will be able to save time and energy as they can continue to work without having to stop and erase. From our research others have attempted to construct similar products. We intend to improve these thoughts and designs in order to build a better and more efficient product

Does My Dog ''Speak'' Like Me? The Acoustic Correlation between Pet Dogs and Their Human Owners

How hosts language influence their pets' vocalization is an interesting yet underexplored problem. This paper presents a preliminary investigation into the possible correlation between domestic dog vocal expressions and their human host's language environment. We first present a new dataset of Shiba Inu dog vocals from YouTube, which provides 7500 clean sound clips, including their contextual information of these vocals and their owner's speech clips with a carefully-designed data processing pipeline. The contextual information includes the scene category in which the vocal was recorded, the dog's location and activity. With a classification task and prominent factor analysis, we discover significant acoustic differences in the dog vocals from the two language environments. We further identify some acoustic features from dog vocalizations that are potentially correlated to their host language patterns

Quadruped Pupper Robotics: Dynamics and Control

The purpose of this project is to provide insights on the Pupper Robot, from Hands-On Robotics (handsonrobotics.org), for future studies and research. The Hands-On Robotics (HOR) team aims to provide robotics kits and educational curricula to explore agile locomotion, motor control, and AI for community colleges and high schools. We worked with the HOR team in this project to help them better achieve their goals. The main objectives of this project include: 1. Build the robot and analyze the dynamical behaviors of the robot. 2. Investigate the robot control from both hardware and software perspectives. 3. Design a new gait for the Pupper Robot. 4. Create an implementation guide for future groups, documenting knowledge we have learned during the project. By the end of this project, we achieved the following: A. Built a fully functioning robot. B. Investigated the theoretical underpinnings of quadruped robots, including inverse kinematics and gait generation theories. C. Understood and reflected on the control structure of the robot. D. Implemented a new jumping gait which allows the robot to leap forward and land on balance. E. Composed detailed guides on robot building instructions, controller files installation, simulator installation, and simulator modifications

Towards Lexical Analysis of Dog Vocalizations via Online Videos

Deciphering the semantics of animal language has been a grand challenge. This study presents a data-driven investigation into the semantics of dog vocalizations via correlating different sound types with consistent semantics. We first present a new dataset of Shiba Inu sounds, along with contextual information such as location and activity, collected from YouTube with a well-constructed pipeline. The framework is also applicable to other animal species. Based on the analysis of conditioned probability between dog vocalizations and corresponding location and activity, we discover supporting evidence for previous heuristic research on the semantic meaning of various dog sounds. For instance, growls can signify interactions. Furthermore, our study yields new insights that existing word types can be subdivided into finer-grained subtypes and minimal semantic unit for Shiba Inu is word-related. For example, whimper can be subdivided into two types, attention-seeking and discomfort

The bacterial effectors EspG and EspG2 induce a destructive calpain activity that is kept in check by the co-delivered Tir effector

Bacterial pathogens deliver multiple effector proteins into eukaryotic cells to subvert host cellular processes and an emerging theme is the cooperation between different effectors. Here, we reveal that a fine balance exists between effectors that are delivered by enteropathogenic E. coli (EPEC) which, if perturbed can have marked consequences on the outcome of the infection. We show that absence of the EPEC effector Tir confers onto the bacterium a potent ability to destroy polarized intestinal epithelia through extensive host cell detachment. This process was dependent on the EPEC effectors EspG and EspG2 through their activation of the host cysteine protease calpain. EspG and EspG2 are shown to activate calpain during EPEC infection, which increases significantly in the absence of Tir – leading to rapid host cell loss and necrosis. These findings reveal a new function for EspG and EspG2 and show that Tir, independent of its bacterial ligand Intimin, is essential for maintaining the integrity of the epithelium during EPEC infection by keeping the destructive activity of EspG and EspG2 in check