From the 1 of 12 linked papers with an AI index.
6 papers · 1 filter
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,…
Prompt-Level Distillation: A Non-Parametric Alternative to Model Fine-Tuning for Efficient Reasoning
Sanket Badhe, Deep Shah
Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inference costs. The standard alternati…
The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods
Sanket Badhe, Priyanka Tiwari, Deep Shah
Large Language Models are increasingly used as zero-shot classifiers in complex reasoning tasks. However, standard constrained decoding suffers from a phenomenon we define as Renor…
CROP: Token-Efficient Reasoning in Large Language Models via Regularized Prompt Optimization
Deep Shah, Sanket Badhe, Nehal Kathrotia +1
Large Language Models utilizing reasoning techniques improve task performance but incur significant latency and token costs due to verbose generation. Existing automatic prompt opt…
Large Language Models in the Abuse Detection Pipeline
Suraj Kath, Sanket Badhe, Preet Shah +2
Online abuse has grown increasingly complex, spanning toxic language, harassment, manipulation, and fraudulent behavior. Traditional machine-learning approaches dependent on static…
Long-Tail Knowledge in Large Language Models: Taxonomy, Mechanisms, Interventions and Implications
Sanket Badhe, Deep Shah, Nehal Kathrotia
Large language models (LLMs) are trained on web-scale corpora that exhibit steep power-law distributions, in which the distribution of knowledge is highly long-tailed, with most ap…