1 citations · 3 across the 30 of their papers we have counts for
33 papers
IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas
Ziyu Chen, Yilun Zhao, Jiashuo Sun +3
Scientific research often begins by synthesizing ideas from a set of related papers to identify gaps and formulate new directions. However, training language models to perform this…
Learning to Ideate for Scientific Impact
Shubham Kale, Aniketh Garikaparthi, Manasi Patwardhan
Scientific ideation is increasingly mediated by large language models, but current ideation systems are usually trained and evaluated on immediately judgeable proxies such as novel…
BackTrend: Evaluating Scientific Weak-Signal Prediction via Backward Reconstruction
Xiao Zhou, Yilun Zhao, Owen Jiang +4
Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet existing resources such as trend tracking, citation…
Surprising Effectiveness of Self-Demonstrations in Enhancing Schema-Ontology Mapping with LLMs
Siddhesh Thombre, Manasi Patwardhan, Sunita Sarawagi
Integrating heterogeneous relational databases into a centralized ontology remains a persistent challenge in enterprise knowledge representation, primarily due to semantic heteroge…
IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications
Yiling Ma, Yilun Zhao, Sihong Wu +2
A research idea may be novel, coherent, and scientifically plausible, yet its proposed method may remain insufficiently specified for faithful implementation. We study the codifica…
ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation
Yiling Ma, Yilun Zhao, Sihong Wu +3
As LLMs are increasingly used for pre-submission self-review, there is growing demand for feedback that not only identifies weaknesses but also guides authors toward concrete revis…
Can Scientific Claims Be Removed from Large Language Models? A Systematic Evaluation of Claim-Level Unlearning
Snigdha Paul, Manasi Patwardhan, Arman Cohan
Language models (LMs) are trained on static scientific corpora, whereas scientific knowledge continuously evolves through correction and revision. Scientific claims encoded within…
Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results
Jan Batzner, Sree Harsha Nelaturu, Damian Stachura +45
AI evaluations are widely used for testing and understanding progress. However, the diverse evaluators bring with them inconsistencies that challenge analysis and comparison. First…
Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future
Sihong Wu, Owen Jiang, Yilun Zhao +5
Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLM…
SciMDR: Advancing Scientific Multimodal Document Reasoning
Ziyu Chen, Yilun Zhao, Chengye Wang +3
Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faithfulness, and realism. To address this…
RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation
Sihong Wu, Yiling Ma, Yilun Zhao +4
Large language models (LLMs) are increasingly used across the scientific workflow, including to draft peer-review reports. However, many AI-generated reviews are superficial and in…
Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation
Srujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan
As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and filtering hundreds of AI-generate…
Defend: Automated Rebuttals for Peer Review with Minimal Author Guidance
Jyotsana Khatri, Manasi Patwardhan
Rebuttal generation is a critical component of the peer review process for scientific papers, enabling authors to clarify misunderstandings, correct factual inaccuracies, and guide…
ResearchGym: Evaluating Language Model Agents on Real-World AI Research
Aniketh Garikaparthi, Manasi Patwardhan, Arman Cohan
We introduce ResearchGym, a benchmark and execution environment for evaluating AI agents on end-to-end research. To instantiate this, we repurpose five oral and spotlight papers fr…
REVERE: Reflective Evolving Research Engineer
Balaji Dinesh Gangireddi, Aniketh Garikaparthi, Manasi Patwardhan +1
Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks. In addition, they also rely on weak update mechanisms, such as full-prompt…
Routing End User Queries to Enterprise Databases
Saikrishna Sudarshan, Tanay Kulkarni, Manasi Patwardhan +3
We address the task of routing natural language queries in multi-database enterprise environments. We construct realistic benchmarks by extending existing NL-to-SQL datasets. Our s…
Quality Detection of Stored Potatoes via Transfer Learning: A CNN and Vision Transformer Approach
Shrikant Kapse, Priyankkumar Dhrangdhariya, Priya Kedia +5
Image-based deep learning provides a non-invasive, scalable solution for monitoring potato quality during storage, addressing key challenges such as sprout detection, weight loss e…
SciRAG: Adaptive, Citation-Aware, and Outline-Guided Retrieval and Synthesis for Scientific Literature
Hang Ding, Yilun Zhao, Tiansheng Hu +2
The accelerating growth of scientific publications has intensified the need for scalable, trustworthy systems to synthesize knowledge across diverse literature. While recent retrie…
Privacy Preserving Ordinal-Meta Learning with VLMs for Fine-Grained Fruit Quality Prediction
Riddhi Jain, Manasi Patwardhan, Aayush Mishra +2
To effectively manage the wastage of perishable fruits, it is crucial to accurately predict their freshness or shelf life using non-invasive methods that rely on visual data. In th…
Thought-For-Food: Reasoning Chain Induced Food Visual Question Answering
Riddhi Jain, Manasi Patwardhan, Parijat Deshpande +1
The immense diversity in the culture and culinary of Indian cuisines calls attention to the major shortcoming of the existing Visual Question Answering(VQA) systems which are incli…
Retrieval and Augmentation of Domain Knowledge for Text-to-SQL Semantic Parsing
Manasi Patwardhan, Ayush Agarwal, Shabbirhussain Bhaisaheb +3
The performance of Large Language Models (LLMs) for translating Natural Language (NL) queries into SQL varies significantly across databases (DBs). NL queries are often expressed u…
MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems
Sri Ram Macharla, Sridhar Murthy J, Anjaneyulu Pasala
MultiFluxAI is an innovative AI platform developed to address the challenges of managing and integrating vast, disparate data sources in product engineering across application doma…
AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research
Yilun Zhao, Weiyuan Chen, Zhijian Xu +5
We introduce AbGen, the first benchmark designed to evaluate the capabilities of LLMs in designing ablation studies for scientific research. AbGen consists of 1,500 expert-annotate…
Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers
Zhijian Xu, Yilun Zhao, Manasi Patwardhan +2
Peer review is fundamental to scientific research, but the growing volume of publications has intensified the challenges of this expertise-intensive process. While LLMs show promis…