Feb. 28, 2024, 5:49 a.m. | Orion Weller, Dawn Lawrie, Benjamin Van Durme

cs.CL updates on arXiv.org arxiv.org

arXiv:2305.07614v2 Announce Type: replace-cross
Abstract: Negation is a common everyday phenomena and has been a consistent area of weakness for language models (LMs). Although the Information Retrieval (IR) community has adopted LMs as the backbone of modern IR architectures, there has been little to no research in understanding how negation impacts neural IR. We therefore construct a straightforward benchmark on this theme: asking IR models to rank two documents that differ only by negation. We show that the results vary …

abstract architectures arxiv community consistent cs.cl cs.ir impacts information language language models lms modern research retrieval the information type understanding

Data Scientist (m/f/x/d)

@ Symanto Research GmbH & Co. KG | Spain, Germany

Data Science Analyst I - Pulmonary

@ Mount Sinai Health System | United States

Data Engineering, Lead

@ Booz Allen Hamilton | USA, GA, Atlanta (1349 W Peachtree St NW)

Data Science Recruiter (US Hiring)

@ Tiger Analytics | India - Remote

Business Intelligence Analyst (I, II, III, Senior)

@ C Spire | Ridgeland, MS, United States

Senior Staff Infrastructure Engineer (Data Infrastructure)

@ Coupang | Seattle, USA