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Found 14 papers, 5 papers with code
Rule Based Event Extraction for Artificial Social Intelligence
Natural language (as opposed to structured communication modes such as Morse code) is by far the most common mode of communication between humans, and can thus provide significant insight into both individual mental states and interpersonal dynamics.
When and Where Did it Happen? An Encoder-Decoder Model to Identify Scenario Context
We introduce a neural architecture finetuned for the task of scenario context generation: The relevant location and time of an event or entity mentioned in text.
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games
In this paper, we investigate the semantic clustering properties of deep reinforcement learning (DRL) for video games, enriching our understanding of the internal dynamics of DRL and advancing its interpretability.
Hierarchical Fusion for Online Multimodal Dialog Act Classification
We propose a framework for online multimodal dialog act (DA) classification based on raw audio and ASR-generated transcriptions of current and past utterances.
Ranked #1 on
Dialogue Act Classification
on EMOTyDA
Probabilistic Modeling of Human Teams to Infer False Beliefs
We find that the players' behaviors are affected by what they see in their in-game field of view, their beliefs about the meaning of the markers, and their beliefs about which meaning the team decided to adopt.
Using Features at Multiple Temporal and Spatial Resolutions to Predict Human Behavior in Real Time
We contend that for an artificially intelligent agent to effectively model human teammates, i. e., demonstrate computational theory of mind (ToM), it should do the same.
Deep Reinforcement Learning with Vector Quantized Encoding
Human decision-making often involves combining similar states into categories and reasoning at the level of the categories rather than the actual states.
Modular Procedural Generation for Voxel Maps
The benefits of this approach include rapid, scalable, and efficient development of virtual environments, the ability to control the statistics of the environment at a semantic level, and the ability to generate novel environments in response to player actions in real time.
MathAlign: Linking Formula Identifiers to their Contextual Natural Language Descriptions
Extending machine reading approaches to extract mathematical concepts and their descriptions is useful for a variety of tasks, ranging from mathematical information retrieval to increasing accessibility of scientific documents for the visually impaired.
AutoMATES: Automated Model Assembly from Text, Equations, and Software
Models of complicated systems can be represented in different ways - in scientific papers, they are represented using natural language text as well as equations.
Eidos, INDRA, \& Delphi: From Free Text to Executable Causal Models
Building causal models of complicated phenomena such as food insecurity is currently a slow and labor-intensive manual process.
Exotic Higgs Decays in Type-II 2HDMs at the LHC and Future 100 TeV Hadron Colliders
The exotic decay modes of non-Standard Model (SM) Higgses in models with extended Higgs sectors have the potential to serve as powerful search channels to explore the space of Two-Higgs Doublet Models (2HDMs) that cannot be studied effectively using conventional decay channels.
High Energy Physics - Phenomenology
