2 citations · 3 across the 5 of their papers we have counts for
3 papers · 1 filter
TituLLMs: A Family of Bangla LLMs with Comprehensive Benchmarking
Shahriar Kabir Nahin, Rabindra Nath Nandi, Sagor Sarker +7
In this paper, we present TituLLMs, the first large pretrained Bangla LLMs, available in 1b and 3b parameter sizes. Due to computational constraints during both training and infere…
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations
Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov +2
A major barrier towards the practical deployment of large language models (LLMs) is their lack of reliability. Three situations where this is particularly apparent are correctness,…
WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models
Youssef Benchekroun, Megi Dervishi, Mark Ibrahim +7
We propose WorldSense, a benchmark designed to assess the extent to which LLMs are consistently able to sustain tacit world models, by testing how they draw simple inferences from…