Embodied CAD deploys solver-grounded LLM agents with stratified L0-L4 skills, action grammar, and solver rewards to achieve high executable rates on multi-step mechanical and mold assembly tasks.
Advances in Neural Information Processing Systems , year =
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PROTEA supplies an offline interface for scoring intermediate outputs in multi-agent LLM workflows, performing backward evaluation from final answers, and iterating on targeted prompt revisions with visible score changes.
A separate memory agent that selectively injects reminders into an unmodified action agent improves long-horizon task performance by up to 8.3 percentage points.
A structured Research Question Certificate improves the judged quality and auditability of LLM-proposed scientific questions, per a small LLM-judge evaluation.
Causal Memory Intervention selects memories based on estimated causal impact on LLM answers rather than semantic similarity, with a new benchmark showing improved robustness to irrelevant or harmful memories.
citing papers explorer
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Embodied CAD: Solver-Grounded LLM Agents for Parametric B-Rep Assembly Modeling
Embodied CAD deploys solver-grounded LLM agents with stratified L0-L4 skills, action grammar, and solver rewards to achieve high executable rates on multi-step mechanical and mold assembly tasks.
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PROTEA: Offline Evaluation and Iterative Refinement for Multi-Agent LLM Workflows
PROTEA supplies an offline interface for scoring intermediate outputs in multi-agent LLM workflows, performing backward evaluation from final answers, and iterating on targeted prompt revisions with visible score changes.
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Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
A separate memory agent that selectively injects reminders into an unmodified action agent improves long-horizon task performance by up to 8.3 percentage points.
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FirstResearch: Auditable Question Formation for LLM Scientific Discovery Agents
A structured Research Question Certificate improves the judged quality and auditability of LLM-proposed scientific questions, per a small LLM-judge evaluation.
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Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents
Causal Memory Intervention selects memories based on estimated causal impact on LLM answers rather than semantic similarity, with a new benchmark showing improved robustness to irrelevant or harmful memories.