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Siddhant Bharti

3 accepted papers

2025

Tool Preferences in Agentic LLMs are Unreliable

EMNLP 2025

Large language models (LLMs) can now access a wide range of external tools, thanks to the Model Context Protocol (MCP). This greatly expands their abilities as various agents. However, LLMs rely entirely on the text descriptions of tools to decide which ones to use—a process that is surprisingly fra

2024

LLM-Check: Investigating Detection of Hallucinations in Large Language Models

NeurIPS 2024poster

While Large Language Models (LLMs) have become immensely popular due to their outstanding performance on a broad range of tasks, these models are prone to producing hallucinations— outputs that are fallacious or fabricated yet often appear plausible or tenable at a glance. In this paper, we conduct…

Cited by 143SourcePDFScholar
2020

An Inference Algorithm for Multi-Label MRF-MAP Problems with Clique Size 100

ECCV 2020poster

In this paper, we propose an algorithm for optimal solutions to submodular higher-order multi-label MRF-MAP energy functions which can handle practical computer vision problems with up to 16 labels and cliques of size 100. The algorithm uses a transformation which transforms a multi-label problem to…