activity
20102026
most citedHow to Escape Saddle Points Efficiently

229 citations · 1.5k across the 69 of their papers we have counts for

collaborators

76 papers

hep-th2026

TheoPhysEval: Assessing AI agents at autonomous theoretical physics problem solving

A. Ramesh Chandra, Aaghaz Mahajan, Ainesh Sanyal +32

We present a suite of 50 unpublished research-level theoretical physics problems with verifiable answers. Without AI assistance, a typical problem in our collection could be solved…

astro-ph.SR2026

Period spacings and global seismic parameters for K2 red giants using deep learning

Nipun Ghanghas, Siddharth Dhanpal, Shravan Hanasoge +2

Gravity-mode period spacings (DPi_1) of red giants probe the stellar core directly, constraining its structure, mass and evolutionary state. Their measurement requires resolving na…

cs.LG2026

A model of errors in transformers

Suvrat Raju, Praneeth Netrapalli

We study the error rate of LLMs on tasks like arithmetic that require a deterministic output, and repetitive processing of tokens drawn from a small set of alternatives. We argue t…

cs.LG2025

Compressing Many-Shots in In-Context Learning

Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta +9

Large Language Models (LLMs) have been shown to be able to learn different tasks without explicit finetuning when given many input-output examples / demonstrations through In-Conte…

cs.LG2025

Spark Transformer: Reactivating Sparsity in FFN and Attention

Chong You, Kan Wu, Zhipeng Jia +16

The discovery of the lazy neuron phenomenon in trained Transformers, where the vast majority of neurons in their feed-forward networks (FFN) are inactive for each token, has spurre…

cs.LG2025

A Faster Generalized Two-Stage Approximate Top-K

Yashas Samaga, Varun Yerram, Spandana Raj Babbula +2

We consider the Top- selection problem, which aims to identify the largest elements in an array. Top- selection arises in many machine learning algorithms and often becom…