We show that proving exponential lower bounds on depth four arithmetic circuits imply for unrestricted circuits. In other words, sized additional beyond does not help. then a complete black-box derandomization of identity testing problem with multiplication gates small fanin implies nearly general testing.

Recent advances in contrastive representation learning over paired image-text data have led to models such as CLIP that achieve state-of-the-art performance for zero-shot classification and distributional robustness. Such typically require joint reasoning the image text spaces downstream inference tasks. Contrary prior beliefs, we demonstrate representations learned via a standard objective are not interchangeable can lead inconsistent predictions. To mitigate this issue, formalize...

Evaluation in Information Retrieval (IR) has long focused on effectiveness and efficiency. However, new emerging access tasks now demand alternative evaluation measures which go beyond this traditional view. A retrieval system provides a means of gaining to documents, therefore intuitively, our view the collection is shaped by system. In paper, we outline some information related scenarios that require knowledge about how affects users' ability information. This motivation for proposed...

Recent work has shown that more effective dense retrieval models can be obtained by distilling ranking knowledge from an existing base re-ranking model. In this paper, we propose a generic curriculum learning based optimization framework called CL-DRD controls the difficulty level of training data produced (teacher) iteratively optimizes (student) model increasing distillation made available to it. detail, initially provide student coarse-grained preference pairs between documents in...

The author examines various counting measures on space bounded nondeterministic auxiliary pushdown machines. In the main theorem, it is shown how a NAuxPDA may be simulated efficiently by uniform family of Boolean circuits, which preserve number accepting paths in as subtrees circuit. techniques used simulate novel way considering height and reversal bounds an AuxPDA. One highlights present work exact characterization important class DET. It that DET exactly functions can computed difference...

There is a growing interest in estimating the effectiveness of search. Two approaches are typically considered: examining search queries and retrieved document sets. In this paper, we take latter approach. We use four measures to characterize sets estimate quality These (i) clustering tendency as measured by Cox-Lewis statistic, (ii) sensitivity perturbation, (iii) query perturbation (iv) local intrinsic dimensionality. present experimental results for task ranking 200 according over TREC...

Many web systems rank and present a list of items to users, from recommender search advertising. An important problem in practice is evaluate new ranking policies offline optimize them before they are deployed. We address this by proposing evaluation algorithms for estimating the expected number clicks on ranked lists historical logged data. The existing not guaranteed be statistically efficient our because recommended can grow exponentially with their length. To overcome challenge, we use...

Crawl selection policy has a direct influence on Web search effectiveness, because useful page that is not selected for crawling will also be absent from results. Yet there been little or no work measuring this effect. We introduce an evaluation framework, based relevance judgments pooled multiple engines, the maximum potential NDCG achievable using particular crawl. This allows us to evaluate different crawl policies and investigate important scenarios like stability over iterations....

We evaluate three different relevance feedback (RF)algorithms, Rocchio, Robertson/Sparck-Jones (RSJ)and Bayesian, in the context of Web search. use a target-testing experimental procedure whereby user must locate specific document. For feedback, we consider all possible choices indicating zero or more relevant documents from set 10 displayed documents. Examination effects each choice permits us to compute an upper-bound on performance RF algorithm.We ind that there is significant variation o...

The growth of digital information increases the need to build better techniques for automatically storing, organizing and retrieving it. Much this is textual in nature existing representation models struggle deal with high dimensionality resulting feature space. Techniques like latent semantic indexing address, some degree, problem retrieval. However, promising alternatives, random mapping (RM), have yet be completely studied context. In paper, we show that despite attention RM has received...

We consider the problem of optimally allocating a fixed budget to construct test collection with associated relevance judgements, such that it can (i) accurately evaluate relative performance participating systems, and (ii) generalize new, previously unseen systems. propose two stage approach. For given set queries, we adopt traditional pooling method use portion documents retrieved by Next, analyze judgments prioritize queries remaining pooled for further assessments. The query...

Scene graphs are a powerful structured representation of the underlying content images, and embeddings derived from them have been shown to be useful in multiple downstream tasks. In this work, we employ graph convolutional network exploit structure scene produce image for semantic retrieval. Different classification-centric supervision traditionally available learning representations, address task relative similarity labels ranking context. Rooted within contrastive paradigm, propose novel...