A toolbox for benchmarking trustworthiness of multimodal large language models (MultiTrust, NeurIPS 2024 Track Datasets and Benchmarks)

Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

[ICML'2024] Can AI Assistants Know What They Don't Know?

A toolbox for benchmarking Multimodal LLM Agents trustworthiness across truthfulness, controllability, safety and privacy dimensions through 34 interactive tasks

Unofficial implementation of Microsoft’s Claimify Paper: extracts specific, verifiable, decontextualized claims from LLM Q&A to be used for Hallucination, Groundedness, Relevancy and Truthfulness detection

Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood Consistency

Google Chrome Extension to add LLM text reading in a browser

Improving LLM truthfulness via reporting confidence

Example VerityIndex Reports on Media

A research project on competing notions of truth in large language models.

My first eval / interpretability project. Testing steering vectors for truthfulness and honesty on TruthfulQA and MASK.

Behavioral auditing toolkit for LLMs: rho-audit measures factual accuracy, bias, sycophancy, toxicity, and reasoning via teacher-forced confidence probes. SVD compression with knowledge preservation. Steering vectors for runtime behavioral control. 12-model merge audit across SLERP/TIES/DARE-TIES/Linear.