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This paper presents a pruning method, Reconstruction Error Aware Pruning (REAP), to reduce the redundancy of convolutional neural network models for accelerating the inference. REAP is an extension of one of the state-of-the-art channel pruning…
This paper presents a pruning method, Reconstruction Error Aware Pruning (REAP), to reduce the redundancy of convolutional neural network models for accelerating the inference. REAP is an extension of one of the state-of-the-art channel pruning…
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Agent Trading Arena probes numerical understanding of LLM-based trading agents in a zero-sum market simulation
InvestorBench evaluates LLM-based agents on financial decision-making tasks across multiple asset classes and markets
FinMTEB is a finance-specific massive text embedding benchmark with 64 datasets across seven financial NLP task types
