3 citations · 4 across the 10 of their papers we have counts for
5 papers · 1 filter
MAPLE: A Multimodal Mobile Agent with Playbook-Learned Experience
Jun Wang, Aurora Wei, Lucas Spangher +3
Autonomous agents powered by vision-language models (VLMs) show great potential in navigating mobile graphical user interfaces (GUIs) to complete complex tasks. However, existing p…
AutoScientist-Quant: Self-Evolving Coding Agents for Automatic Research in Quantitative Investment
Zongqian Li, Yaoyiran Li, Yaohui Guo +3
Large language model agents can discover alphas, yet current methods have three weaknesses. The search cannot adapt during the run, automation usually ends at alpha generation whil…
WebRider: Persona-Conditioned Intent Controllers for Live-Web Assistance
Zhi Li, Tao Zhou, Yeqing Li +2
Delegating a web task involves more than asking a question; it requires transferring a policy: what to verify, how to handle uncertainty, which preferences matter, and when to stop…
How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum
Chu-Cheng Lin, Eugene Ie
The standard recipe for training reasoning models---SFT on rationale annotations followed by RLVR---relies on rationale annotations being available and clean. When no annotated rat…
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…