output
20102026
most citedThe Large Hadron-Electron Collider at the HL-LHC

244 citations

Showing cs.CLShow all

6 papers · 1 filter

cs.CL2026

Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say "I Don't Know"

Dhruv Madhwal, Lyuxin David Zhang, Dan Roth +2

Large language models often struggle to recognize their knowledge limits in closed-book question answering, leading to confident hallucinations. While decomposed prompting is typic…

cs.CL2024★ 30 cited

Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly

With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes domains, ensuring the trustworthiness, safety, and observability of these systems has b…

cs.CL2021

Automatic Post-Editing for Vietnamese

Thanh Vu, Dai Quoc Nguyen

Automatic post-editing (APE) is an important remedy for reducing errors of raw translated texts that are produced by machine translation (MT) systems or software-aided translation.…

cs.CL2021★ 6 cited

Optimizing Inference Performance of Transformers on CPUs

Dave Dice, Alex Kogan

The Transformer architecture revolutionized the field of natural language processing (NLP). Transformers-based models (e.g., BERT) power many important Web services, such as search…

cs.CL2020★ 4 cited

Detecting and Exorcising Statistical Demons from Language Models with Anti-Models of Negative Data

Michael L. Wick, Kate Silverstein, Jean-Baptiste Tristan +2

It's been said that "Language Models are Unsupervised Multitask Learners." Indeed, self-supervised language models trained on "positive" examples of English text generalize in desi…

cs.CL2018★ 21 cited

A Survey on Semantic Parsing

Aishwarya Kamath, Rajarshi Das

A significant amount of information in today's world is stored in structured and semi-structured knowledge bases. Efficient and simple methods to query them are essential and must…