9 papers
DataProphet: Demystifying Supervision Data Generalization in Multimodal LLMs
Xuan Qi, Luxi He, Dan Roth +1
Conventional wisdom for selecting supervision data for multimodal large language models (MLLMs) is to prioritize datasets that appear similar to the target benchmark, such as text-…
Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills
Pengcheng Jiang, Jiacheng Lin, Zhiyi Shi +31
Large language model (LLM) agents are moving beyond prompting alone. ChatGPT marked the rise of general-purpose LLM assistants, DeepSeek showed that on-policy reinforcement learnin…
AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
Jinghang Shi, Xiaoyu Tang, Yang Huang +4
Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…
The Model Hears You: Audio Language Model Deployments Should Consider the Principle of Least Privilege
Luxi He, Xiangyu Qi, Michel Liao +4
The latest Audio Language Models (Audio LMs) process speech directly instead of relying on a separate transcription step. This shift preserves detailed information, such as intonat…
Statutory Construction and Interpretation for Artificial Intelligence
Luxi He, Nimra Nadeem, Michel Liao +4
AI systems are increasingly governed by natural language principles, yet a key challenge arising from reliance on language remains underexplored: interpretive ambiguity. As in lega…
Metadata Conditioning Accelerates Language Model Pre-training
Tianyu Gao, Alexander Wettig, Luxi He +3
The vast diversity of styles, domains, and quality levels present in language model pre-training corpora is essential in developing general model capabilities, but efficiently lear…