12 citations · 13 across the 13 of their papers we have counts for
8 papers · 1 filter
EMPATH: A Multilingual Auditor-Judge Benchmark for Safety Evaluation of Emotional-Support Chatbots
Camilo Chacón Sartori
Safety benchmarks often buy scalability by fixing the prompt, the language, and the turn structure. For emotional-support chatbots, that bargain hides precisely where safety failur…
A Fixed-Budget, Cluster-Aware Standard for LLM-as-a-Judge Evaluation: A Multi-Hop RAG Stress Test
Camilo Chacón Sartori, José H. García
Retrieval-augmented generation (RAG) systems are often compared by asking a large language model (LLM) judge which answer is better. For multi-hop RAG, this has become a measuremen…
Transferable knowledge graphs with executable learned operators for algorithm design
Camilo Chacón Sartori, José H. García, Andrei Voicu Tomut +1
Procedural knowledge in algorithm design is embedded in source code and rebuilt for each new domain. We introduce Generative Executable Algorithm Knowledge Graphs (GEAKG), a repres…
Architectures of Error: A Philosophical Inquiry into AI and Human Code Generation
Camilo Chacón Sartori
With the rise of generative AI (GenAI), Large Language Models are increasingly employed for code generation, becoming active co-authors alongside human programmers. Focusing specif…
Combinatorial Optimization for All: Using LLMs to Aid Non-Experts in Improving Optimization Algorithms
Camilo Chacón Sartori, Christian Blum
Large Language Models (LLMs) have shown notable potential in code generation for optimization algorithms, unlocking exciting new opportunities. This paper examines how LLMs, rather…
Improving Existing Optimization Algorithms with LLMs
Camilo Chacón Sartori, Christian Blum
The integration of Large Language Models (LLMs) into optimization has created a powerful synergy, opening exciting research opportunities. This paper investigates how LLMs can enha…
Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach
Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa +1
Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algo…
Large Language Models for the Automated Analysis of Optimization Algorithms
Camilo Chacón Sartori, Christian Blum, Gabriela Ochoa
The ability of Large Language Models (LLMs) to generate high-quality text and code has fuelled their rise in popularity. In this paper, we aim to demonstrate the potential of LLMs…