Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method

Kavli Affiliate: Wei Gao | First 5 Authors: Xuan Zhang, Wei Gao, , , | Summary: While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still under-explored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find […]


Continue.. Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method

Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities

Kavli Affiliate: Wei Gao | First 5 Authors: Haoming Wang, Wei Gao, , , | Summary: The efficiency of Federated Learning (FL) is often affected by both data and device heterogeneities. Data heterogeneity is defined as the heterogeneity of data distributions on different clients. Device heterogeneity is defined as the clients’ variant latencies in uploading […]


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Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Hanyun Yin, Heng Huang, Wei Gao, | Summary: Fine-tuning is the most effective way of adapting pre-trained large language models (LLMs) to downstream applications. With the fast growth of LLM-enabled AI applications and democratization of open-souced LLMs, fine-tuning has become possible for non-expert individuals, but […]


Continue.. Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

Kavli Affiliate: Wei Gao | First 5 Authors: Kai Huang, Hanyun Yin, Heng Huang, Wei Gao, | Summary: Fine-tuning is the most effective way of adapting pre-trained large language models (LLMs) to downstream applications. With the fast growth of LLM-enabled AI applications and democratization of open-souced LLMs, fine-tuning has become possible for non-expert individuals, but […]


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Deep Learning with Photonic Neural Cellular Automata

Kavli Affiliate: Alireza Marandi | First 5 Authors: Gordon H. Y. Li, Christian R. Leefmans, James Williams, Robert M. Gray, Midya Parto | Summary: Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable hardware. Photonics offers a promising solution by leveraging the unique properties of light. […]


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ICM-SHOX. Paper I: Methodology overview and discovery of a gas–dark matter velocity decoupling in the MACS J0018.5+1626 merger

Kavli Affiliate: Sunil Golwala | First 5 Authors: Emily M. Silich, Elena Bellomi, Jack Sayers, John ZuHone, Urmila Chadayammuri | Summary: Galaxy cluster mergers are rich sources of information to test cluster astrophysics and cosmology. However, cluster mergers produce complex projected signals that are difficult to interpret physically from individual observational probes. Multi-probe constraints on […]


Continue.. ICM-SHOX. Paper I: Methodology overview and discovery of a gas–dark matter velocity decoupling in the MACS J0018.5+1626 merger

Taking the Milky Way for a spin: disc formation in the ARTEMIS simulations

Kavli Affiliate: Andrey Kravtsov | First 5 Authors: Adam M. Dillamore, Vasily Belokurov, Andrey Kravtsov, Andreea S. Font, | Summary: We investigate the formation (spin-up) of galactic discs in the ARTEMIS simulations of Milky Way-mass galaxies. In almost all galaxies discs spin up at higher [Fe/H] than the Milky Way (MW). Those that contain an […]


Continue.. Taking the Milky Way for a spin: disc formation in the ARTEMIS simulations

Taking the Milky Way for a spin: disc formation in the ARTEMIS simulations

Kavli Affiliate: Andrey Kravtsov | First 5 Authors: Adam M. Dillamore, Vasily Belokurov, Andrey Kravtsov, Andreea S. Font, | Summary: We investigate the formation (spin-up) of galactic discs in the ARTEMIS simulations of Milky Way-mass galaxies. In almost all galaxies discs spin up at higher [Fe/H] than the Milky Way (MW). Those that contain an […]


Continue.. Taking the Milky Way for a spin: disc formation in the ARTEMIS simulations