🧑‍🔬 Manasi Patwardhan

🏛️ Affiliations

🏢Tata Consultancy ServicesPune · India2026 · 4 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers (2025 · 11 citations)
   Peer review is increasingly strained as publication volume grows. Existing benchmarks for LLM-generated reviews mostly judge overall review quality and pay little attention to whether models can find a paper's real weaknesses. This work isolates that skill. The authors first build a taxonomy of limitation types for…
2. AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research (2025 · 9 citations)
   AbGen tests whether large language models can help scientists plan experiments, focusing on ablation study design.
3. SciRAG: Adaptive, Citation-Aware, and Outline-Guided Retrieval and Synthesis for Scientific Literature (2026 · 7 citations)
   Scientific output keeps growing quickly, and existing retrieval-augmented generation (RAG) tools for literature QA have four main weaknesses.
4. RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation (2026 · 2 citations)
   LLM-drafted peer reviews often sound fluent but stay generic, so authors get little guidance they can actually implement.
5. Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future (2026 · 1 citation)
   This survey asks how far large language models can support or automate scholarly peer review. It treats review as a full pipeline (reviewing, rebuttal, meta-review, decision, and revision) rather than a single text-generation step. The authors build a taxonomy across three areas:
6. Routing End User Queries to Enterprise Databases (2026)
   The paper studies database routing: given a natural-language question and a large set of enterprise databases, rank the databases by how likely each one can answer it.
7. Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation (2026)
   AI research agents can produce hundreds of candidate ideas, but testing each one experimentally is impractical.

🤝 Co-authors here

12 co-authors with a page, the most papers together first.

• Arman Cohan ×5
• Yilun Zhao ×5
• Lovekesh Vig ×3
• Tiansheng Hu ×3
• Owen Jiang ×2
• Sihong Wu ×2
• Yiling Ma ×2
• Zhijian Xu ×2
• Chengye Wang
• Hang Ding
• Kaiyan Zhang
• Yixin Liu

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL) ×3: ACL 2026, ACL 2025 ×2
• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026
• Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era: Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era 2026

🔗 Cited by

Papers of our library cite their works 17 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated 1 November 2026

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