24 citations · 32 across the 11 of their papers we have counts for
11 papers
Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings
Yidong Jiang, Junrong Chen, Eftychia Makri +7
With the increasing deployment of Large Language Models (LLMs) in the finance domain, LLMs are increasingly expected to parse complex regulatory disclosures. However, existing benc…
Adaptation of Embedding Models to Financial Filings via LLM Distillation
Eliot Brenner, Dominic Seyler, Manjunath Hegde +3
Despite advances in generative large language models (LLMs), practical application of specialized conversational AI agents remains constrained by computation costs, latency require…
Long Document Summarization in a Low Resource Setting using Pretrained Language Models
Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna +7
Abstractive summarization is the task of compressing a long document into a coherent short document while retaining salient information. Modern abstractive summarization methods ar…
End-to-End Neural Ranking for eCommerce Product Search: an application of task models and textual embeddings
Eliot Brenner, Jun Zhao, Aliasgar Kutiyanawala +1
We consider the problem of retrieving and ranking items in an eCommerce catalog, often called SKUs, in order of relevance to a user-issued query. The input data for the ranking are…
Incorporating Type II Error Probabilities from Independence Tests into Score-Based Learning of Bayesian Network Structure
Eliot Brenner, David Sontag
We give a new consistent scoring function for structure learning of Bayesian networks. In contrast to traditional approaches to score-based structure learning, such as BDeu or MDL,…
SparsityBoost: A New Scoring Function for Learning Bayesian Network Structure
Eliot Brenner, David Sontag
We give a new consistent scoring function for structure learning of Bayesian networks. In contrast to traditional approaches to scorebased structure learning, such as BDeu or MDL,…