3 papers
cs.CL2026
Do Factuality Methods Make LLMs More Factual? Reproducibility and Fair Comparison
Pratuat Amatya, Vinay Setty, V Venktesh +1
Large Language Models (LLMs) are aligned to human preferences, after pre-training and supervised fine-tuning steps. However, standard RL alignment steps such as RLHF do not focus o…
cs.CL2026
Calibrating Small Language Models for Claim Check-Worthiness Detection
Pratuat Amatya, V Venktesh, Vinay Setty
Assessing claim check-worthiness is an essential first step in automated fact-checking pipelines. This work is motivated by a real deployment challenge at an early-stage startup: r…
cs.CL2026
Multilingual Fact-Checking at Scale: Fine-Tuned Compact Models vs LLMs
Pratuat Amatya, Vinay Setty
We present a multilingual fact-checking system deployed at Factiverse, designed for high-throughput and low-latency operation across diverse languages. The system follows a modular…