Skip to content

Add Team 8 Paper Link to README #497

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
DhavalRepo18 merged 1 commit into from
Aug 2, 2026
Merged

Add Team 8 Paper Link to README #497

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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)
Expand Down