MemGym unifies agent gyms into a memory benchmark with isolated scoring across tool-use, research, coding, and computer-use regimes plus a lightweight reward model for tractable coding evaluation.
Selective classification for deep neural networks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
SABER combines self-prior with multi-trace PK and CK reasoning representations to estimate reliability beliefs and drive trust-or-abstain decisions in knowledge-conflict RAG, improving accuracy over baselines.
citing papers explorer
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MemGym: a Long-Horizon Memory Environment for LLM Agents
MemGym unifies agent gyms into a memory benchmark with isolated scoring across tool-use, research, coding, and computer-use regimes plus a lightweight reward model for tractable coding evaluation.
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Trust or Abstain? A Self-Aware RAG Approach
SABER combines self-prior with multi-trace PK and CK reasoning representations to estimate reliability beliefs and drive trust-or-abstain decisions in knowledge-conflict RAG, improving accuracy over baselines.