MIRAI: Evaluating LLM Agents for Event Forecasting
We introduce MIRAI, a benchmark crafted for evaluating LLM agents in temporal forecasting of international events with tool use and complex reasoning. With 59,161 unique events and 296,630 unique news articles, we curate a test set of 705 forecasting query-answer pairs.
Jul 1, 2024
Enhancing Large Vision Language Models with Self-Training on Image Comprehension
We introduce STIC (Self-Training on Image Comprehension) that enhances the understanding and reasoning capabilities of LVLMs through self-generated data. Our experiments across seven benchmarks, including ScienceQA, TextVQA, ChartQA, LLaVA-Bench, MMBench, MM-Vet, and MathVista, demonstrate a notable average accuracy gain of 4.0% by self-training.
May 30, 2024
Mitigating object hallucination in large vision-language models via classifier-free guidance
Feb 13, 2024
Robust learning with progressive data expansion against spurious correlation
Jan 1, 2024
Rephrase and respond: Let large language models ask better questions for themselves
Nov 7, 2023
PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning
Oct 1, 2023
Towards understanding the mixture-of-experts layer in deep learning
Jan 1, 2022
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Sep 1, 2015