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Instead of mimicking gold-standard examples, MLLMs reason significantly better when shown suboptimal outputs alongside explicit contrastive paths to correct them.
SciLENS outperforms existing models in scientific literature synthesis by leveraging structural visualization to enhance reasoning and context retention.
Gradient-Aligned Reward transforms how we leverage expert knowledge in reinforcement learning, enabling LLMs to achieve superior reasoning performance with minimal overhead.
