Fluent but Fallible: Benchmarking Hallucination and Factual Reliability in Large Language Models
arXiv:2610.27034v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly advanced natural language processing and artificial intelligence applications through their capabilities in reasoning, text generation and knowledge retrieval. However, LLMs are still vulnerable to two i…
Read the full story at arXiv cs.CL ↗
Timeline · 1 report
- 2026-10-21 04:00 · arXiv cs.CL
Fluent but Fallible: Benchmarking Hallucination and Factual Reliability in Large Language Models