9 citations · 18 across the 23 of their papers we have counts for
5 papers · 1 filter
CausalDS: Benchmarking Causal Reasoning in Data-Science Agents
Andrej Leban, Yuekai Sun, Theo Saarinen
Large language models (LLMs) increasingly act as data-science agents, combining abstract reasoning with advanced tool use. Yet the relevant benchmark landscape largely divides into…
From Reasoning Traces to Reusable Modules: Understanding Compositional Generalization in Language Model Reasoning
Lingjing Kong, Xin Liu, Guangyi Chen +9
Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming large language models (LLMs) into…
LeanMarathon: Toward Reliable AI Co-Mathematicians through Long-Horizon Lean Autoformalization
Yuanhe Zhang, Yuekai Sun, Taiji Suzuki +2
Long-horizon autoformalization of research mathematics fails not only at hard lemmas, but at scale: statements drift, dependencies tangle, context decays, and local repairs corrupt…
The Open Source Economic Index of AI Adoption and Capability
Seamus Somerstep, Aritra Guha, Divesh Srivastava +1
We work towards measuring both AI adoption and the capability of AI to perform discrete labor tasks across various occupations. To measure adoption, we develop an open-source econo…
K2-V2: A 360-Open, Reasoning-Enhanced LLM
K2 Team, Zhengzhong Liu, Liping Tang +36
We introduce K2-V2, a 360-open LLM built from scratch as a superior base for reasoning adaptation, in addition to functions such as conversation and knowledge retrieval from genera…