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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Lingdong Shen

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Sep 2026

Advancing Scientific Chart Understanding: The SCI-CQA Benchmark and Beyond.

In real-world applications, current multimodal large models are often overestimated in their ability to understand scientific charts. To assess their true capabilities and identify key performance bottlenecks, we conducted an in-depth study on scientific chart understanding. Charts in scientific literature often featur...

Ling-Dong Shen, Qigqi, Kun Ding et al. · 0 citations
Book Open access Aug 2026

The Forgetting-Learning Trade-off: Making Reinforcement Learning Work for Protein Language Models

Diagnostics reveal that RL on PLMs is governed by two reward properties: verifiability, whether the reward is a fixed environment or a learned surrogate vulnerable to distribution shift, and coverage, the fraction of sequence space giving an informative gradient.

Hanqun Cao, Hongrui Zhang, Junde Xu et al. · 0 citations
Book Open access Aug 2026

The Forgetting-Learning Trade-off: Making Reinforcement Learning Work for Protein Language Models

Reinforcement learning (RL) is increasingly applied to Protein Language Models (PLMs), yet its effectiveness varies across tasks, and standard metrics such as pass@k can rise even when the model's solvable problem set is shrinking. We introduce two capability-level diagnostics. The Expansion-Shrinkage Ratio (ESR) measu...

Hanqun Cao, Hongrui Zhang, Junde Xu et al. · 0 citations

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