activity
20232025
most citedHumanity's Last Exam

23 citations · 33 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2025★ 23 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1168

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.AI2024★ 2 cited

Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark

Himanshu Gupta, Shreyas Verma, Ujjwala Anantheswaran +4

Multi-modal Large Language Models (MLLMs) exhibit impressive problem-solving abilities in various domains, but their visual comprehension and abstract reasoning skills remain under…

cs.CL2024

Cutting Through the Noise: Boosting LLM Performance on Math Word Problems

Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria +3

Large Language Models (LLMs) excel at various tasks, including solving math word problems (MWPs), but struggle with real-world problems containing irrelevant information. To addres…

cs.CL2023★ 3 cited

TarGEN: Targeted Data Generation with Large Language Models

Himanshu Gupta, Kevin Scaria, Ujjwala Anantheswaran +5

The rapid advancement of large language models (LLMs) has sparked interest in data synthesis techniques, aiming to generate diverse and high-quality synthetic datasets. However, th…

cs.CL2023

EDM3: Event Detection as Multi-task Text Generation

Ujjwala Anantheswaran, Himanshu Gupta, Mihir Parmar +2

Event detection refers to identifying event occurrences in a text and comprises of two subtasks; event identification and classification. We present EDM3, a novel approach for Even…

cs.CL2023★ 5 cited

Exploring the Limits of Transfer Learning with Unified Model in the Cybersecurity Domain

Kuntal Kumar Pal, Kazuaki Kashihara, Ujjwala Anantheswaran +3

With the increase in cybersecurity vulnerabilities of software systems, the ways to exploit them are also increasing. Besides these, malware threats, irregular network interactions…