Papers by Aleksandar Fontana
On the Hidden Objective Biases of Group-based Reinforcement Learning (2026.acl-short)
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| Challenge: | Recent studies have reported unexpected behaviors during training, including lengthrelated biases, formatting tokens, and reward hacking in multi-objective settings. |
| Approach: | They propose to analyze group-based reinforcement learning methods within a unified surrogate formulation. |
| Outcome: | The proposed methods exhibit structural mismatches between reward optimization and the underlying training objective. |