works on

From the 1 of 8 linked papers with an AI index.

activity
20242026
collaborators

8 papers

math.CT2026

Left properness of Moore flows

Philippe Gaucher

We introduce the notion of a reparametrization category with cuts. For every such reparametrization category , we prove the tensor lemma, namely that the tensor product…

cs.LG2026

Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning

Xin Qiu, Yulu Gan, Conor F. Hayes +6

The paper shows that evolution strategies can successfully fine‑tune billion‑parameter large language models without backpropagation, outperforming reinforcement learning in stabil…

cs.NE2026

Fine-Tuning Language Models to Know What They Know

Sangjun Park, Elliot Meyerson, Xin Qiu +1

Evaluating true metacognition in Large Language Models (LLMs) is difficult due to biases and heuristics. This paper presents a framework to measure and enhance LLM metacognition wh…

cs.IR2026

Caesar: Deep Agentic Web Exploration for Creative Answer Synthesis

Jason Liang, Elliot Meyerson, Risto Miikkulainen

To advance from passive retrieval to creative discovery of new ideas, autonomous agents must be capable of deep, associative synthesis. However, current agentic frameworks prioriti…

cs.AI2025

Solving a Million-Step LLM Task with Zero Errors

Elliot Meyerson, Giuseppe Paolo, Roberto Dailey +6

LLMs have achieved remarkable breakthroughs in reasoning, insights, and tool use, but chaining these abilities into extended processes at the scale of those routinely executed by h…

cs.CL2025

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Elliot Meyerson, Xin Qiu

Decomposing hard problems into subproblems often makes them easier and more efficient to solve. With large language models (LLMs) crossing critical reliability thresholds for a gro…