1 citations · 1 across the 7 of their papers we have counts for
7 papers
Predictive Coding and Information Bottleneck for Hallucination Detection in Large Language Models
Manish Bhatt
Hallucinations in Large Language Models (LLMs) -- generations that are plausible but factually unfaithful -- remain a critical barrier to high-stakes deployment. Current detection…
Large Empirical Case Study: Go-Explore adapted for AI Red Team Testing
Manish Bhatt, Adrian Wood, Idan Habler +1
Production LLM agents with tool-using capabilities require security testing despite their safety training. We adapt Go-Explore to evaluate GPT-4o-mini across 28 experimental runs s…
MAIF: Enforcing AI Trust and Provenance with an Artifact-Centric Agentic Paradigm
Vineeth Sai Narajala, Manish Bhatt, Idan Habler +2
The AI trustworthiness crisis threatens to derail the artificial intelligence revolution, with regulatory barriers, security vulnerabilities, and accountability gaps preventing dep…
Logic layer Prompt Control Injection (LPCI): A Novel Security Vulnerability Class in Agentic Systems
Hammad Atta, Ken Huang, Manish Bhatt +3
The integration of large language models (LLMs) into enterprise systems has introduced a new class of covert security vulnerabilities, particularly within logic execution layers an…
Bhatt Conjectures: On Necessary-But-Not-Sufficient Benchmark Tautology for Human Like Reasoning
Manish Bhatt
The Bhatt Conjectures framework introduces rigorous, hierarchical benchmarks for evaluating AI reasoning and understanding, moving beyond pattern matching to assess representation…
COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents
Manish Bhatt, Ronald F. Del Rosario, Vineeth Sai Narajala +1
The meteoric rise and proliferation of autonomous Large Language Model (LLM) agents promise significant capabilities across various domains. However, their deployment is increasing…