TeamTR is a trust-region framework for multi-agent LLM fine-tuning that resamples trajectories after each update to convert quadratic compounding occupancy shift into linear scaling and yields per-update improvement lower bounds.
International Conference on Learning Representations (ICLR) , year =
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Pith papers citing it
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
EfficientTDMPC extends the TD-MPC family with model ensembles, return averaging, and uncertainty penalties to reach SOTA sample efficiency on hard continuous control benchmarks in low-data regimes.
citing papers explorer
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TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
TeamTR is a trust-region framework for multi-agent LLM fine-tuning that resamples trajectories after each update to convert quadratic compounding occupancy shift into linear scaling and yields per-update improvement lower bounds.
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EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control
EfficientTDMPC extends the TD-MPC family with model ensembles, return averaging, and uncertainty penalties to reach SOTA sample efficiency on hard continuous control benchmarks in low-data regimes.