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20232026
most citedAgent-as-a-Judge: Evaluate Agents with Agents

3 citations · 6 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.AI2024

How to Correctly do Semantic Backpropagation on Language-based Agentic Systems

Wenyi Wang, Hisham A. Alyahya, Dylan R. Ashley +4

Language-based agentic systems have shown great promise in recent years, transitioning from solving small-scale research problems to being deployed in challenging real-world tasks.…

cs.LG2024

Automatic Album Sequencing

Vincent Herrmann, Dylan R. Ashley, Jürgen Schmidhuber

Album sequencing is a critical part of the album production process. Recently, a data-driven approach was proposed that sequences general collections of independent media by extrac…

cs.AI2024★ 3 cited

Agent-as-a-Judge: Evaluate Agents with Agents

Mingchen Zhuge, Changsheng Zhao, Dylan Ashley +10

Contemporary evaluation techniques are inadequate for agentic systems. These approaches either focus exclusively on final outcomes -- ignoring the step-by-step nature of agentic sy…

cs.LG2024

Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning

Yuhui Wang, Qingyuan Wu, Dylan R. Ashley +4

The Value Iteration Network (VIN) is an end-to-end differentiable neural network architecture for planning. It exhibits strong generalization to unseen domains by incorporating a d…

cs.RO2024

Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms

Mohannad Alhakami, Dylan R. Ashley, Joel Dunham +4

Advanced machine learning algorithms require platforms that are extremely robust and equipped with rich sensory feedback to handle extensive trial-and-error learning without relyin…