  Several tools have recently been proposed for assisting researchers during
various stages of the research life-cycle. However, these primarily concentrate
on tasks such as retrieving and recommending relevant literature, reviewing and
critiquing the draft, and writing of research manuscripts. Our investigation
reveals a significant gap in availability of tools specifically designed to
assist researchers during the challenging ideation phase of the research
life-cycle. To aid with research ideation, we propose `Acceleron', a research
accelerator for different phases of the research life cycle, and which is
specially designed to aid the ideation process. Acceleron guides researchers
through the formulation of a comprehensive research proposal, encompassing a
novel research problem. The proposals motivation is validated for novelty by
identifying gaps in the existing literature and suggesting a plausible list of
techniques to solve the proposed problem. We leverage the reasoning and
domain-specific skills of Large Language Models (LLMs) to create an agent-based
architecture incorporating colleague and mentor personas for LLMs. The LLM
agents emulate the ideation process undertaken by researchers, engaging
researchers in an interactive fashion to aid in the development of the research
proposal. Notably, our tool addresses challenges inherent in LLMs, such as
hallucinations, implements a two-stage aspect-based retrieval to manage
precision-recall trade-offs, and tackles issues of unanswerability. As
evaluation, we illustrate the execution of our motivation validation and method
synthesis workflows on proposals from the ML and NLP domain, given by 3
distinct researchers. Our observations and evaluations provided by the
researchers illustrate the efficacy of the tool in terms of assisting
researchers with appropriate inputs at distinct stages and thus leading to
improved time efficiency.
