Consider the "Number in Hand" multiparty communication complexity model, where k players holding inputs x 1 , . . . , x k ∈ {0, 1} n communicate to compute the value f (x 1 , . . . , x k ) of a function f known to all of them. The main lower bound technique for the communication complexity of such problems is that of partition arguments: partition the k players into two disjoint sets of players and find a lower bound for the induced two-party communication complexity problem. In this paper, we

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... tudy the power of partition arguments. Our two main results are very different in nature: (i) For randomized communication complexity, we show that partition arguments may yield bounds that are exponentially far from the true communication complexity. Specifically, we prove that there exists a 3-argument function f whose communication complexity is Ω(n), while partition arguments can only yield an Ω(log n) lower bound. The same holds for nondeterministiccommunication complexity. (ii) For deterministic communication complexity, we prove that finding significant gaps between the true communication complexity and the best lower bound that can be obtained via partition arguments, would imply progress on a generalized version of the "log-rank conjecture" in communication complexity. We also observe that, in the case of computing relations (search problems), very large gaps do exist. We conclude with two results on the multiparty "fooling set technique", another method for obtaining communication complexity lower bounds.