Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models Paper • 2410.02740 • Published Oct 3 • 52
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging Paper • 2410.01215 • Published Oct 2 • 30
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models Paper • 2409.17146 • Published Sep 25 • 99
Beyond Fine-tuning: Unleashing the Potential of Continuous Pretraining for Clinical LLMs Paper • 2409.14988 • Published Sep 23 • 21
MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines Paper • 2409.12959 • Published Sep 19 • 36
Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers Paper • 2409.04109 • Published Sep 6 • 43
Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise Paper • 2410.03017 • Published Oct 3 • 25
Addition is All You Need for Energy-efficient Language Models Paper • 2410.00907 • Published Oct 1 • 143
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations Paper • 2410.02707 • Published Oct 3 • 47
RevisEval: Improving LLM-as-a-Judge via Response-Adapted References Paper • 2410.05193 • Published 30 days ago • 12