From 6ee2dc72a4ada277d031ed9adc5d7a086e919353 Mon Sep 17 00:00:00 2001 From: Rohith Kanathur Date: Fri, 31 Jul 2026 09:58:15 -0400 Subject: [PATCH] Add Team 8 paper link to README Signed-off-by: Rohith Kanathur --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 1e9f04080..219606172 100644 --- a/README.md +++ b/README.md @@ -254,7 +254,7 @@ AssetOpsBench is being extended by university research groups exploring new asse - **Calibrated Coordination Reduces Overconfident Errors in Multi-Agent LLM Systems** – Confidence-weighted aggregation and abstention framework for reducing hallucinated confidence events in multi-agent industrial troubleshooting and operational decision-making benchmarks. Chand Sahil Mansuri, Sadamori Kojaku, Binghamton University. - **Internalizing MCP Tool Knowledge in Small LLMs via QLoRA Fine-Tuning** — HPML project using AssetOpsBench to fine-tune ~4B models to internalize MCP tool knowledge and reduce prompt schema overhead. [Ayal Yakobe](https://github.com/yakobeayal), Columbia University · [repo](https://github.com/YuvalShemla/hpml-2026-project) - **SPIN — Structural LLM Planning via Iterative Navigation for Industrial Tasks.** [Yusuke Ozaki](https://github.com/ozatamago), University at Albany · [paper](https://arxiv.org/abs/2605.14051) · [repo](https://github.com/ozatamago/AssetOpsBench/tree/UACap10) -- **Synthetic Scenario Generation for Evaluation of Industry 4.0 Agents** — Automated scenario generation, transformer asset integration, and scenario quality evaluation. [Rohith Kanathur](https://github.com/Rohith-Kanathur), [Sagar Chethan Kumar](https://github.com/Sagar-CK), Columbia University · [repo](https://github.com/Rohith-Kanathur/AssetOpsBench) +- **Synthetic Scenario Generation for Evaluation of Industry 4.0 Agents** — Automated scenario generation, transformer asset integration, and scenario quality evaluation. [Rohith Kanathur](https://github.com/Rohith-Kanathur), [Sagar Chethan Kumar](https://github.com/Sagar-CK), Columbia University · [repo](https://github.com/Rohith-Kanathur/AssetOpsBench) · [paper](https://arxiv.org/abs/2607.22563) - **AgentOpsBench** — High-throughput battery analytics MCP server with DNN prognostics (RUL prediction) and 3.3× latency optimization. [Siddharth Gowda, Rushin Bhatt, Aryaman Agrawal, Winston Li](https://github.com/siddharthgowda), Columbia University · [repo](https://github.com/siddharthgowda/AssetOpsBench) - **Skill-Knowledge-Augmented Agents on AssetOpsBench** — Confidence-gated skill execution with scoped knowledge plugins for industrial fault diagnosis. [Vera Mazeeva](https://github.com/verammaz), [Sanskruti Shejwal](https://github.com/Sans-Shej), [Shrey Arora](https://github.com/shreyarora2198), [Mana Abbaszadeh](https://github.com/Manazd), Columbia University · [repo](https://github.com/shreyarora2198/AssetOpsBench/tree/team14-final) - **Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines.** [Krish Veera](https://www.github.com/krishrveera/), [Alimurtaza Mustafa Merchant](https://github.com/alimurtaza0411/), [Sajal Kumar Goyla](https://github.com/SajalGoyla/), [Shambhawi Bhure](https://github.com/ShambhawiBhure/), Columbia University · [paper](https://arxiv.org/abs/2605.20630) · [repo](https://github.com/alimurtaza0411/Latency-Optimized-AssetOpsBench/tree/feature/ablation-study)