Papers by Mert Yuksekgonul
Inefficiencies of Meta Agents for Agent Design (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Recent work has automated the design of agentic systems using meta-agents . authors examine three key challenges in a common class of meta-gents. |
| Approach: | They examine how meta-agents learn across iterations and show performance improves with evolutionary approach. |
| Outcome: | The proposed meta-agents perform worse when iterating on multiple agents than human-designed agents. |
Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory (2026.eacl-long)
Copied to clipboard
| Challenge: | Unlike fine-tuning or static retrieval methods, DC adapts LMs’ problem-solving skills on the fly, without modifying their underlying parameters. |
| Approach: | They propose a lightweight framework that endows a black-box LM with a persistent, evolving memory. |
| Outcome: | The proposed framework enables models to store and reuse accumulated strategies, code snippets, and general problem-solving insights at inference time. |