3 papers
cs.LG2026
Self-Improvement as Coherence Optimization: A Theoretical Account
Tianyi Qiu, Ahmed Hani Ismail, Zhonghao He +1
Can language models improve their accuracy without external supervision? Methods such as debate, bootstrap, and internal coherence maximization achieve this surprising feat, even m…
cs.AI2026
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…
cs.AI2025
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…