A new robust variant of MCTS that mitigates dynamical model ambiguities to bridge the gap between simulation-based planning and real-world deployment and empirical evidence is provided that this method achieves robust performance in planning problems even under significant ambiguity in the underlying reward distributio...
T. Dam, Kishan Panaganti, Brahim Driss et al.· International Conference on...· 5 citations· ⚡1
FlowBalance, a verifier-grounded self-improvement method that learns a normalized distribution over complete responses, improves average performance over FlowRL on both Qwen3-4B and Qwen3-8B, while also improving training speed and stability, avoiding direct OPSD's response-length collapse, and exhibiting higher correc...
Zi-Xun Huang, Kishan Panaganti, Hai-Tao Mi et al.· 0 citations
The capability of a modern AI agent depends not only on its foundation model but also on its harness, which constructs prompts, manages state, invokes tools, and coordinates execution. As models, APIs, environments, and requirements evolve, the harness must be continually modified. Before such a change can be made, a d...
Ruhan Wang, Yucheng Shi, Zongxia Li et al.· 7 citations
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