activity
20242026
most citedINCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

4 citations · 6 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Spatial Reasoning is Not a Free Lunch: A Controlled Study on LLaVA

Nahid Alam, Leema Krishna Murali, Siddhant Bharadwaj +7

Vision-language models (VLMs) have advanced rapidly, yet they still struggle with basic spatial reasoning. Despite strong performance on general benchmarks, modern VLMs remain brit…

cs.CV2026

The Spatial Blindspot of Vision-Language Models

Nahid Alam, Leema Krishna Murali, Siddhant Bharadwaj +7

Vision-language models (VLMs) have advanced rapidly, but their ability to capture spatial relationships remains a blindspot. Current VLMs are typically built with contrastive langu…

cs.CV2025

Behind Maya: Building a Multilingual Vision Language Model

Nahid Alam, Karthik Reddy Kanjula, Surya Guthikonda +16

In recent times, we have seen a rapid development of large Vision-Language Models (VLMs). They have shown impressive results on academic benchmarks, primarily in widely spoken lang…

cs.CL2025

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42

The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…

cs.CL2025★ 1 cited

Robust and Fine-Grained Detection of AI Generated Texts

Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Kanwal Mehreen +12

An ideal detection system for machine generated content is supposed to work well on any generator as many more advanced LLMs come into existence day by day. Existing systems often…

cs.CL2025

Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance

Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Siddhant Gupta +6

Large Language Models (LLMs) have shown remarkable capabilities, but their development has primarily focused on English and other high-resource languages, leaving many languages un…

cs.CV2024

Maya: An Instruction Finetuned Multilingual Multimodal Model

Nahid Alam, Karthik Reddy Kanjula, Surya Guthikonda +16

The rapid development of large Vision-Language Models (VLMs) has led to impressive results on academic benchmarks, primarily in widely spoken languages. However, significant gaps r…

cs.CL2024

1-800-SHARED-TASKS at RegNLP: Lexical Reranking of Semantic Retrieval (LeSeR) for Regulatory Question Answering

Jebish Purbey, Drishti Sharma, Siddhant Gupta +3

This paper presents the system description of our entry for the COLING 2025 RegNLP RIRAG (Regulatory Information Retrieval and Answer Generation) challenge, focusing on leveraging…

cs.CL2024

SeQwen at the Financial Misinformation Detection Challenge Task: Sequential Learning for Claim Verification and Explanation Generation in Financial Domains

Jebish Purbey, Siddhant Gupta, Nikhil Manali +4

This paper presents the system description of our entry for the COLING 2025 FMD challenge, focusing on misinformation detection in financial domains. We experimented with a combina…

cs.CL2024★ 4 cited

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Angelika Romanou, Negar Foroutan, Anna Sotnikova +56

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…

cs.CL2024★ 1 cited

1-800-SHARED-TASKS @ NLU of Devanagari Script Languages: Detection of Language, Hate Speech, and Targets using LLMs

Jebish Purbey, Siddartha Pullakhandam, Kanwal Mehreen +4

This paper presents a detailed system description of our entry for the CHiPSAL 2025 shared task, focusing on language detection, hate speech identification, and target detection in…

cs.CL2024

M-RewardBench: Evaluating Reward Models in Multilingual Settings

Srishti Gureja, Lester James V. Miranda, Shayekh Bin Islam +7

Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the language modeling process. However, RMs are pr…