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Home/Authors/Sarbartha Banerjee

Sarbartha Banerjee

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
0

Publications per year

2
26

Top categories

AI×2ML×2Multiagent×1Distributed×1

Frequent co-authors

Souvik Kundu2×
Tushar Krishna2×
Ritik Raj1×
Dheemanth Joshi1×
Ishita Vohra1×
Hanjiang Wu1×

Research Timeline

2026
How Far Can Disaggregation Go? A Design-Space Exploration of Attention-FFN Disaggregation for Efficient MoE LLM Serving

The paper systematically analyzes the benefits and limits of Attention-FFN Disaggregation (AFD) for Mixture-of-Experts (MoE) LLM serving, demonstrating that AFD is crucial for achieving high throughput under strict latency constraints.

TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI

The paper introduces TRACE-Router, a task-level routing framework for large language models that aligns routing with the unit of supervision using delayed task feedback.

Highlighted terms show continued research focus across papers

Papers

cs.AIcs.LGcs.MAEmpiricalRecentJul 24, 2026

TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI

Ritik Raj, Souvik Kundu, Sarbartha Banerjee, Dheemanth Joshi +2 more

The paper introduces TRACE-Router, a task-level routing framework for large language models that aligns routing with the unit of supervision using delayed task feedback.

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cs.LGcs.AIcs.DCRecent
May 27, 2026

How Far Can Disaggregation Go? A Design-Space Exploration of Attention-FFN Disaggregation for Efficient MoE LLM Serving

Hanjiang Wu, Abhimanyu Rajeshkumar Bambhaniya, Sarbartha Banerjee, Tuhin Khare +8 more

The paper systematically analyzes the benefits and limits of Attention-FFN Disaggregation (AFD) for Mixture-of-Experts (MoE) LLM serving, demonstrating that AFD is crucial for achieving high throughpu…

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