5 citations · 8 across the 5 of their papers we have counts for
7 papers
Metacognitive Reasoning in Energy Based Models using Instance Based Learning Theory
Tailia Malloy, Prateek Kumar Rajput, Serge Lionel Nikiema +2
Metacognition involves reasoning about cognitive processes themselves. An example is in resource allocation where we choose how much time and effort to put into a reasoning task be…
Trajectory-Level Security Debt in LLM Coding Agents
Prateek Kumar Rajput, Abdoul Kader Kabore, Yewei Song +4
LLM coding agents can traverse hundreds of intermediate code states before submitting a solution. Evaluating only the final artifact leaves the evolution of security findings unmea…
Assessing Spear-Phishing Website Generation in Large Language Model Coding Agents
Tailia Malloy, Tegawende F. Bissyande
Large Language Models are expanding beyond being a tool humans use and into independent agents that can observe an environment, reason about solutions to problems, make changes tha…
Modeling Attention during Dimensional Shifts with Counterfactual and Delayed Feedback
Tailia Malloy, Roderick Seow, Cleotilde Gonzalez
Attention can be used to inform choice selection in contextual bandit tasks even when context features have not been previously experienced. One example of this is in dimensional s…
Learning in Factored Domains with Information-Constrained Visual Representations
Tailia Malloy, Miao Liu, Matthew D. Riemer +3
Humans learn quickly even in tasks that contain complex visual information. This is due in part to the efficient formation of compressed representations of visual information, allo…
Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games
Tailia Malloy, Tim Klinger, Miao Liu +3
This paper introduces an information-theoretic constraint on learned policy complexity in the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorit…
Deep RL With Information Constrained Policies: Generalization in Continuous Control
Tailia Malloy, Chris R. Sims, Tim Klinger +3
Biological agents learn and act intelligently in spite of a highly limited capacity to process and store information. Many real-world problems involve continuous control, which rep…