59 citations · 211 across the 39 of their papers we have counts for
6 papers · 1 filter
ASTRA-bench: Evaluating Tool-Use Agent Reasoning and Action Planning with Personal User Context
Zidi Xiu, David Q. Sun, Kevin Cheng +9
Next-generation AI must manage vast personal data, diverse tools, and multi-step reasoning, yet most benchmarks remain context-free and single-turn. We present ASTRA-bench (Assista…
Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab
Haonan Duan, Stephen Zhewen Lu, Caitlin Fiona Harrigan +5
Designing experiments and result interpretations are core scientific competencies, particularly in biology, where researchers perturb complex systems to uncover the underlying syst…
Self-Evolving Curriculum for LLM Reasoning
Xiaoyin Chen, Jiarui Lu, Minsu Kim +6
Reinforcement learning (RL) has proven effective for fine-tuning large language models (LLMs), significantly enhancing their reasoning abilities in domains such as mathematics and…
MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains
Guoli Yin, Haoping Bai, Shuang Ma +21
Recent advances in large language models (LLMs) have increased the demand for comprehensive benchmarks to evaluate their capabilities as human-like agents. Existing benchmarks, whi…
Apple Intelligence Foundation Language Models
Tom Gunter, Zirui Wang, Chong Wang +152
We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large serv…
CREAD: Combined Resolution of Ellipses and Anaphora in Dialogues
Bo-Hsiang Tseng, Shruti Bhargava, Jiarui Lu +4
Anaphora and ellipses are two common phenomena in dialogues. Without resolving referring expressions and information omission, dialogue systems may fail to generate consistent and…