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>_ AI RESEARCH <br/>
<span class="text-gray-600">LLMs • Agents • Evaluation • Data</span>
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<span class="text-blue-400">return</span> {<br/>
<span class="text-purple-400">"accuracy"</span>: calculate_metrics(),<br/>
<span class="text-purple-400">"robustness"</span>: stress_test()<br/>
}<br/><br/>
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<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">LLMs</span>
<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">Evaluation</span>
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<h3 class="text-xl font-bold mb-2">Beyond Accuracy: Comprehensive LLM Evaluation</h3>
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Implementing multi-dimensional evaluation frameworks that go beyond simple accuracy metrics to assess model robustness, bias, and reasoning capabilities.
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<span>2023-06-15</span>
<span class="mx-2">•</span>
<span>12 min read</span>
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<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">Agents</span>
<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">Architecture</span>
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<h3 class="text-xl font-bold mb-2">Building Stateful AI Agents</h3>
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Architectural patterns for creating agents with memory and learning capabilities using transformer-based models and reinforcement learning.
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<span>2023-05-28</span>
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<span>15 min read</span>
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Techniques for generating high-quality synthetic training data using LLMs, with quality control mechanisms and diversity metrics.
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<span>2023-04-12</span>
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<span>10 min read</span>
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<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">Evaluation</span>
<span class="tag text-xs font-medium px-2.5 py-0.5 rounded">Metrics</span>
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<h3 class="text-xl font-bold mb-2">Dynamic Evaluation Frameworks</h3>
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Creating adaptive evaluation systems that evolve with model capabilities, focusing on edge cases and failure modes.
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<span>2023-03-05</span>
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<span>8 min read</span>
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<span class="text-green-400"># About the researcher</span><br/>
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<span class="text-blue-400">def</span> __init__(<span class="text-yellow-400">self</span>):<br/>
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<span class="text-purple-400">"Agents"</span>,<br/>
<span class="text-purple-400">"Evaluation"</span><br/>
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I'm an AI researcher and engineer with a focus on developing and evaluating large language models and autonomous agent systems. My work sits at the intersection of machine learning, software engineering, and empirical research methodology.
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Current research interests include:
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<li>Novel evaluation methodologies for generative models</li>
<li>Architectures for long-term memory in AI agents</li>
<li>Scalable synthetic data generation techniques</li>
<li>Failure mode analysis in LLMs</li>
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<li><a href="#" class="hover:text-white">LARGE LANGUAGE MODELS</a></li>
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