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References Improve LLM Alignment in Non-Verifiable Domains
Kejian Shi, Yixin Liu, Peifeng Wang +3
While Reinforcement Learning with Verifiable Rewards (RLVR) has shown strong effectiveness in reasoning tasks, it cannot be directly applied to non-verifiable domains lacking groun…
On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization
Lorenzo Jaime Yu Flores, Arman Cohan
Text summarization and simplification are among the most widely used applications of AI. However, models developed for such tasks are often prone to hallucination, which can result…
Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decoding
Lorenzo Jaime Yu Flores, Heyuan Huang, Kejian Shi +2
Text simplification has emerged as an increasingly useful application of AI for bridging the communication gap in specialized fields such as medicine, where the lexicon is often do…