Useful Summary: In this AI Research Roundup episode, Alex discusses the paper: 'ACC: Compiling Agent Trajectories for Long-Context Title: InstructSAM: Segment Any Instance with Any Instructions (May 2026) Link: Date: May 2026 ...

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  • Title: InstructSAM: Segment Any Instance with Any Instructions (May 2026) Link: Date: May 2026 ...
  • States: Lessons Learned and Key Takeaways," a Research Article in the June ...
  • In this AI Research Roundup episode, Alex discusses the paper: 'ACC: Compiling Agent Trajectories for Long-Context
  • This episode explains arXiv:2605.02105, “Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting.” The paper shows that ...

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Training Compute-Optimal Large Language Models (Chinchilla) - Spring 26' ACM ARC #1 | ACM at ASU
Chinchilla: Training Compute-Optimal Large Language Models
Chinchilla Explained: Compute-Optimal Massive Language Models
Sharpness-Aware Pretraining: Why the Best Base Model Can Forget More
June 2026 CACM: AI Regulation in U.S. States: Lessons Learned and Key Takeaways
InstructSAM: Segment Any Instance with Any Instructions (May 2026)
AcademiClaw: New Academic Benchmark for LLM Agents
ACC: Long-Context LLM Training via Agent Data
USACM. Large Scale Colloquium - Aaditya Chandrasekhar and Brianna Macnider
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Training Compute-Optimal Large Language Models (Chinchilla) - Spring 26' ACM ARC #1 | ACM at ASU

Training Compute-Optimal Large Language Models (Chinchilla) - Spring 26' ACM ARC #1 | ACM at ASU

Read more details and related context about Training Compute-Optimal Large Language Models (Chinchilla) - Spring 26' ACM ARC #1 | ACM at ASU.

Chinchilla: Training Compute-Optimal Large Language Models

Chinchilla: Training Compute-Optimal Large Language Models

Read more details and related context about Chinchilla: Training Compute-Optimal Large Language Models.

Chinchilla Explained: Compute-Optimal Massive Language Models

Chinchilla Explained: Compute-Optimal Massive Language Models

Read more details and related context about Chinchilla Explained: Compute-Optimal Massive Language Models.

Sharpness-Aware Pretraining: Why the Best Base Model Can Forget More

Sharpness-Aware Pretraining: Why the Best Base Model Can Forget More

This episode explains arXiv:2605.02105, “Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting.” The paper shows that ...

June 2026 CACM: AI Regulation in U.S. States: Lessons Learned and Key Takeaways

June 2026 CACM: AI Regulation in U.S. States: Lessons Learned and Key Takeaways

Lavlin Agrawal discusses "AI Regulation in U.S. States: Lessons Learned and Key Takeaways," a Research Article in the June ...

InstructSAM: Segment Any Instance with Any Instructions (May 2026)

InstructSAM: Segment Any Instance with Any Instructions (May 2026)

Title: InstructSAM: Segment Any Instance with Any Instructions (May 2026) Link: Date: May 2026 ...

AcademiClaw: New Academic Benchmark for LLM Agents

AcademiClaw: New Academic Benchmark for LLM Agents

In this AI Research Roundup episode, Alex discusses the paper: 'AcademiClaw: When Students Set Challenges for AI Agents' ...

ACC: Long-Context LLM Training via Agent Data

ACC: Long-Context LLM Training via Agent Data

In this AI Research Roundup episode, Alex discusses the paper: 'ACC: Compiling Agent Trajectories for Long-Context

USACM. Large Scale Colloquium - Aaditya Chandrasekhar and Brianna Macnider

USACM. Large Scale Colloquium - Aaditya Chandrasekhar and Brianna Macnider

May 6, 2026 Dr. Aaditya Chandrasekhar, Northwestern University Topology Optimization of Compositionally Graded Alloys for ...