EngiAI introduces a LangGraph-based multi-agent framework and a three-part benchmark suite for LLM-driven engineering design, reporting high task completion rates for proprietary models on Beams2D and Photonics2D problems.
MCP-Bench: A Benchmark for Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers
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FlowDIS uses flow matching to transport image distributions to mask distributions, optionally conditioned on text, and outperforms prior DIS methods by 5.5% on F_beta^omega and 43% on MAE.
OTCA improves GRPO training for visual generation by estimating step importance in trajectories and adaptively weighting multiple reward objectives.
citing papers explorer
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EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design
EngiAI introduces a LangGraph-based multi-agent framework and a three-part benchmark suite for LLM-driven engineering design, reporting high task completion rates for proprietary models on Beams2D and Photonics2D problems.
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FlowDIS: Language-Guided Dichotomous Image Segmentation with Flow Matching
FlowDIS uses flow matching to transport image distributions to mask distributions, optionally conditioned on text, and outperforms prior DIS methods by 5.5% on F_beta^omega and 43% on MAE.
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Learning to Credit the Right Steps: Objective-aware Process Optimization for Visual Generation
OTCA improves GRPO training for visual generation by estimating step importance in trajectories and adaptively weighting multiple reward objectives.