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20242026
most citedInternational AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management

1 citations · 2 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

Alicia Parrish, Rajat Shinde, Sanket Badhe +57

Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…

cs.CL2025

Where Should I Study? Biased Language Models Decide! Evaluating Fairness in LMs for Academic Recommendations

Krithi Shailya, Akhilesh Kumar Mishra, Gokul S Krishnan +1

Large Language Models (LLMs) are increasingly used as daily recommendation systems for tasks like education planning, yet their recommendations risk perpetuating societal biases. T…

cs.CL2025

IndiCASA: A Dataset and Bias Evaluation Framework in LLMs Using Contrastive Embedding Similarity in the Indian Context

Santhosh G S, Akshay Govind S, Gokul S Krishnan +2

Large Language Models (LLMs) have gained significant traction across critical domains owing to their impressive contextual understanding and generative capabilities. However, their…

cs.CL2025

Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation

Atharvan Dogra, Krishna Pillutla, Ameet Deshpande +5

We explore the ability of large language models (LLMs) to engage in subtle deception through strategically phrasing and intentionally manipulating information. This harmful behavio…

cs.CL2025

LExT: Towards Evaluating Trustworthiness of Natural Language Explanations

Krithi Shailya, Shreya Rajpal, Gokul S Krishnan +1

As Large Language Models (LLMs) become increasingly integrated into high-stakes domains, there have been several approaches proposed toward generating natural language explanations…

cs.CL2025

Multilinguality in LLM-Designed Reward Functions for Restless Bandits: Effects on Task Performance and Fairness

Ambreesh Parthasarathy, Chandrasekar Subramanian, Ganesh Senrayan +4

Restless Multi-Armed Bandits (RMABs) have been successfully applied to resource allocation problems in a variety of settings, including public health. With the rapid development of…