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Markovian with Christian Columbia chr Columbia d

Neural Information Processing Systems

Output: K ?, K ?. 1 for k=1,...,K do 2 Samplez[k] M( |z[k 1]; k 1, k 1) 3 Computes(z[k]; k 1)= r logq(z[k]; k 1) 4 Compute bgML( k 1)= r logp(z[k],x; k 1) 5 Set k= k 1+"ks(z[k]; k 1) 6 Set k= k 1+ kbgML( k 1) 7 end F hood (this obtained or WecompareMSCwith SMC-based [22] using [29].





ConMe: RethinkingEvaluationofCompositional ReasoningforModernVLMs-SupplementaryMaterial-AnonymousAuthor(s) Affiliation Address email

Neural Information Processing Systems

As an example, for an image taken on the ground, two text options24 are: {Several vehicles providing ground transportation are shown in25 the photo: streetcar, tour bus, classic car, and family cars.}