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Merging multiple fine-tuned models is a promising approach for creating a multi-task model, but it suffers from task interference. Our approach, IntervMerge, mitigates this effect stably and efficiently by incorporating mini-interventions.
- Visual-RFT and VisualThinker R1 Zero look promising for visual reasoning. What are your thoughts? arxiv.org/abs/2503.01785 arxiv.org/pdf/2503.05132
- Such a solution seems much more sensible than proper promtting. "LLMs can engage in autonomous dialogue, allowing them to self-discover knowledge and expand their perspectives, leading to a broader spectrum of insights for solving the problem at hand."Replying to @RunzheYangWe implement a multi-agent framework, "SocraticAI"🤖, to solve problems with multiple LLM-based agents collaboratively. Assigning distinct roles, such as 'analysts' or 'proofreaders', allows us to leverage their unique strengths and enhance their overall capabilities as a team.
- George Eustice MP: We made Seaspiracy. Help us protect our oceans from destructive commercial fishing - Sign the Petition! chng.it/2Y8N6yXm przez @Change
- developing successful machine learning applications requires a substantial amount of “black art” that is hard to find in textbooks
