We present the Multi-Modal Discussion Transformer (mDT), a novel method for detecting hate speech on online social networks such as Reddit discussions. In contrast to traditional comment-only methods, our approach labelling comment involves holistic analysis of text and images grounded in discussion context. This is done by leveraging graph transformers capture contextual relationships surrounding grounding interwoven fusion layers that combine image embeddings instead processing modalities...

Citizen-focused democratic processes where participants deliberate on alternatives and then vote to make the final decision are increasingly popular today. While computational social choice literature has extensively investigated voting rules, there is limited work that explicitly looks at interplay of deliberative process voting. In this paper, we build a deliberation model using established models from opinion-dynamics study effect different mechanisms outcomes achieved when well-studied...

Data-centric models of COVID-19 have been attempted, but certain limitations. In this work, we propose an agent-based model the epidemic in a confined space agents representing humans. An extension to SEIR allows us consider difference between appearance (black-box view) spread disease and real situation (glass-box view). Our for simulations lockdowns, social distancing, personal hygiene, quarantine, hospitalization, with further considerations different parameters, such as extent which...

In toy environments like video games, a reinforcement learning agent is deployed and operates within the same state space in which it was trained. However, robotics applications such as industrial systems or autonomous vehicles, this cannot be guaranteed. A robot can pushed out of its training by some unforeseen perturbation, may cause to go into an unknown from has not been trained move towards goal. While most prior work area RL safety focuses on ensuring phase, paper safe deployment that...

Abstract Realistic models of decision-making and social interactions, considering the nature memory biases, continue to be an area immense interest. Emotion mood are a couple key factors that play major role in decisions, size network, level engagement. Most prior work this direction focused on single trait, behavior, or bias. However, builds integrated model considers multiple traits such as loneliness, drive interact, memory, biases agent. The agent system comprises rational, manic,...

ABSTRACT Data-centric models of COVID-19 have been tried, but certain limitations. In this work, we propose an agent-based model the epidemic in a confined space agents representing humans. An extension to SEIR allows us consider difference between appearance (black-box view) spread disease, and real situation (glass-box view). Our for simulations lockdowns, social distancing, personal hygiene, quarantine, hospitalization, with further considerations different parameters such as extent which...

Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out capturing the effects biases humans are susceptible to. This work presents a method to model egocentric bias, real-life tendency emphasize one's own opinion heavily when presented with multiple opinions. We use symmetric distribution centered at agent's opinion, as opposed Bounded Confidence (BC) used in work....

This paper discusses how upper year postsecondary computer science students being educated on social responsibility and AI ethics may benefit from online options for delivery of classes, within discussion-based courses. We reflect the relationship between empathy, learning, including insights provided by published work these topics. draw a course offered in Spring 2022, where had opportunity to experience both in-person when implications computing. Included are few recommendations future...

Citizen-focused democratic processes where participants deliberate on alternatives and then vote to make the final decision are increasingly popular today. While computational social choice literature has extensively investigated voting rules, there is limited work that explicitly looks at interplay of deliberative process voting. In this paper, we build a deliberation model using established models from opinion-dynamics study effect different mechanisms outcomes achieved when well-studied...

We present the Multi-Modal Discussion Transformer (mDT), a novel methodfor detecting hate speech in online social networks such as Reddit discussions. In contrast to traditional comment-only methods, our approach labelling comment involves holistic analysis of text and images grounded discussion context. This is done by leveraging graph transformers capture contextual relationships surrounding grounding interwoven fusion layers that combine image embeddings instead processing modalities...

In toy environments like video games, a reinforcement learning agent is deployed and operates within the same state space in which it was trained. However, robotics applications such as industrial systems or autonomous vehicles, this cannot be guaranteed. A robot can pushed out of its training by some unforeseen perturbation, may cause to go into an unknown from has not been trained move towards goal. While most prior work area RL safety focuses on ensuring phase, paper safe deployment that...

In toy environments like video games, a reinforcement learning agent is deployed and operates within the same state space in which it was trained. However, robotics applications such as industrial systems or autonomous vehicles, this cannot be guaranteed. A robot can pushed out of its training by some unforeseen perturbation, may cause to go into an unknown from has not been trained move towards goal. While most prior work area RL safety focuses on ensuring phase, paper safe deployment that...

In toy environments like video games, a reinforcement learning agent is deployed and operates within the same state space in which it was trained. However, robotics applications such as industrial systems or autonomous vehicles, this cannot be guaranteed. A robot can pushed out of its training by some unforeseen perturbation, may cause to go into an unknown from has not been trained move towards goal. While most prior work area RL safety focuses on ensuring phase, paper safe deployment that...