51 citations · 77 across the 12 of their papers we have counts for
13 papers
Variable Extraction for Model Recovery in Scientific Literature
Chunwei Liu, Enrique Noriega-Atala, Adarsh Pyarelal +2
The global output of academic publications exceeds 5 million articles per year, making it difficult for humans to keep up with even a tiny fraction of scientific output. We need me…
When and Where Did it Happen? An Encoder-Decoder Model to Identify Scenario Context
Enrique Noriega-Atala, Robert Vacareanu, Salena Torres Ashton +3
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. Contextualizing in…
Enhancing Interpretability in Deep Reinforcement Learning through Semantic Clustering
Liang Zhang, Justin Lieffers, Adarsh Pyarelal
In this paper, we explore semantic clustering properties of deep reinforcement learning (DRL) to improve its interpretability and deepen our understanding of its internal semantic…
Probabilistic Modeling of Human Teams to Infer False Beliefs
Paulo Soares, Adarsh Pyarelal, Kobus Barnard
We develop a probabilistic graphical model (PGM) for artificially intelligent (AI) agents to infer human beliefs during a simulated urban search and rescue (USAR) scenario executed…
Multi-Timescale Modeling of Human Behavior
Chinmai Basavaraj, Adarsh Pyarelal, Evan Carter
In recent years, the role of artificially intelligent (AI) agents has evolved from being basic tools to socially intelligent agents working alongside humans towards common goals. I…
Deep Reinforcement Learning with Vector Quantized Encoding
Liang Zhang, Justin Lieffers, Adarsh Pyarelal
Human decision-making often involves combining similar states into categories and reasoning at the level of the categories rather than the actual states. Guided by this intuition,…
Using Features at Multiple Temporal and Spatial Resolutions to Predict Human Behavior in Real Time
Liang Zhang, Justin Lieffers, Adarsh Pyarelal
When performing complex tasks, humans naturally reason at multiple temporal and spatial resolutions simultaneously. We contend that for an artificially intelligent agent to effecti…
Exotic Higgs Decays in the Type-II 2HDMs at Current and Future pp Colliders
Felix Kling, Honglei Li, Shuailong Li +4
The exotic decay modes of non-Standard Model Higgses can serve as powerful search channels to explore the parameter space of extended Higgs sectors. In this Snowmass contribution,…
Modular Procedural Generation for Voxel Maps
Adarsh Pyarelal, Aditya Banerjee, Kobus Barnard
Task environments developed in Minecraft are becoming increasingly popular for artificial intelligence (AI) research. However, most of these are currently constructed manually, thu…
AutoMATES: Automated Model Assembly from Text, Equations, and Software
Adarsh Pyarelal, Marco A. Valenzuela-Escarcega, Rebecca Sharp +6
Models of complicated systems can be represented in different ways - in scientific papers, they are represented using natural language text as well as equations. But to be of real…
Higgs Assisted Razor Search for Higgsinos at a 100 TeV pp Collider
Adarsh Pyarelal, Shufang Su
A 100 TeV proton-proton collider will be an extremely effective way to probe the electroweak sector of the Minimal Supersymmetric Standard Model (MSSM). In this paper, we describe…
Exotic Higgs Decays in Type-II 2HDMs at the LHC and Future 100 TeV Hadron Colliders
Felix Kling, Honglei Li, Adarsh Pyarelal +2
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-…
Light Charged Higgs Bosons to AW/HW via Top Decay
Felix Kling, Adarsh Pyarelal, Shufang Su
While current ATLAS and CMS measurements exclude a light charged Higgs ( GeV) for most of the parameter region in the context of the MSSM scenarios, these bounds are…