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cs.LG2026
Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
Leo Benac, Abhishek Sharma, Alihan Huyuk +1
Inverse reinforcement learning (IRL), which infers reward functions from demonstrations, is a valuable tool for modeling and understanding decision-making behavior. Many variants o…
cs.MA2026
A Benchmark for Multi-Party Negotiation Games from Real Negotiation Data
Leo Benac, Jonas Raedler, Zilin Ma +1
Many real-world multi-party negotiations unfold as sequences of binding, action-level commitments rather than a single final outcome, yet this regime remains under-studied in exist…