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20192026
most citedSAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

123 citations · 215 across the 27 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Recovering Wasted Compute in Autoresearch Agents

Au Kwok Chun, Abhigyan Acherjee, Amrutha Rao +4

A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch. Such agents have inspired large industry invest…

cs.LG2026

The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning

Aakriti Agrawal, Souradip Chakraborty, Armin Saghafian +6

Process Reward Models (PRMs) improve credit assignment for reasoning by providing step-level feedback. However, we identify a hidden bias in PRMs caused by severe imbalance in step…

cs.AI2026

TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting

Sravan Kumar Ankireddy, Nikita Seleznev, Nam H. Nguyen +4

Transformer-based time series foundation models face a fundamental trade-off in choice of tokenization: point-wise embeddings preserve temporal fidelity but scale poorly with seque…

cs.IR2026

Revisiting RAG Retrievers: An Information Theoretic Benchmark

Wenqing Zheng, Dmitri Kalaev, Noah Fatsi +5

Retrieval-Augmented Generation (RAG) systems rely critically on the retriever module to surface relevant context for large language models. Although numerous retrievers have recent…

cs.LG2026

PersonaLedger: Generating Realistic Financial Transactions with Persona Conditioned LLMs and Rule Grounded Feedback

Dehao Yuan, Tyler Farnan, Stefan Tesliuc +8

Strict privacy regulations limit access to real transaction data, slowing open research in financial AI. Synthetic data can bridge this gap, but existing generators do not jointly…