4 citations · 18 across the 27 of their papers we have counts for
4 papers · 1 filter
CBMAS: Cognitive Behavioral Modeling via Activation Steering
Ahmed H. Ismail, Anthony Kuang, Ayo Akinkugbe +2
Large language models (LLMs) often encode cognitive behaviors unpredictably across prompts, layers, and contexts, making them difficult to diagnose and control. We present CBMAS, a…
Reasoning Relay: Evaluating Stability and Interchangeability of Large Language Models in Mathematical Reasoning
Leo Lu, Jonathan Zhang, Sean Chua +4
Chain-of-Thought (CoT) prompting has significantly advanced the reasoning capabilities of large language models (LLMs). While prior work focuses on improving model performance thro…
SMAGDi: Socratic Multi Agent Interaction Graph Distillation for Efficient High Accuracy Reasoning
Aayush Aluru, Myra Malik, Samarth Patankar +4
Multi-agent systems (MAS) often achieve higher reasoning accuracy than single models, but their reliance on repeated debates across agents makes them computationally expensive. We…
SwiftSolve: A Self-Iterative, Complexity-Aware Multi-Agent Framework for Competitive Programming
Adhyayan Veer Singh, Aaron Shen, Brian Law +4
Correctness alone is insufficient: LLM-generated programs frequently satisfy unit tests while violating contest time or memory budgets. We present SwiftSolve, a complexity-aware mu…