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While RLVR improves adherence to environmental constraints and backtracking capabilities, it constricts the space of continuations; we provide evidence suggesting that this might be responsible for the sample efficiency gains of RLVR, albeit at the cost of genuine rollout diversity
from the top result below
https://arxiv.org/list/cs.CL/new
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Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed
https://arxiv.org/list/cs.AI/new
Extending the pattern-generation paradigm of Neural Cellular Automata (NCA), it navigates the degenerate Boolean search space to satisfy a computational task, rather than regenerating a fixed target state
https://arxiv.org/pdf/2407.00345
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https://arxiv.org/pdf/2608.01651v1
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2104.00446
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https://arxiv.org/src/2205.11916v3
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/src/2608.03994
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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/pdf/2608.03883
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2508.04671
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https://arxiv.org/pdf/2303.12712v5
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https://arxiv.org/pdf/2006.04122
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https://arxiv.org/pdf/2608.02615
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https://arxiv.org/html/2608.03048v1
6 million tokens and find that it outperforms the recurrent-memory baseline by +6
https://arxiv.org/html/2608.02613v1
With the interaction history, it co-generates ground truth over six recall, reasoning, and trustworthiness evaluation dimensions
https://arxiv.org/src/2006.02318
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https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/pdf/2407.02402
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https://arxiv.org/pdf/2608.02609
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https://arxiv.org/pdf/2010.15980
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https://arxiv.org/pdf/2608.02618
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https://arxiv.org/pdf/2210.00105
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https://arxiv.org/html/2508.08980v3
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arXiv:2508