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This work proposes a two-agent framework that first identifies the firms for which each alternative data channel is likely to be informative and then predicts revenue using firm- and channel-specific context and evaluates the framework across four commercial alternative data channels.
Get 50% shorter LLM responses without sacrificing accuracy using a new RL method that dynamically balances task reward and length constraints.
