Reconciling Process Supervision with Outcome-Based Credit in Agentic Policy Optimization
Outcome-based reinforcement learning provides verified feedback for language-model agents, but assigns trajectory-lev...
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Outcome-based reinforcement learning provides verified feedback for language-model agents, but assigns trajectory-lev...
Valuable data remains embedded in unstructured sources: web pages, reports, contracts, filings, earnings calls, and P...
Accurate daily predictions of cold hardiness in woody plants are critical in regions where freezing temperatures can ...
Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improveme...
Users of a deployed language model routinely encounter behaviours that testing almost never surfaces, since deploymen...
The effect of Large Language Model (LLM) scale on ontology learning (OL) performance remains insufficiently character...
Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural ali...
The 2025--2026 AI market has seen a wave of stealth releases: frontier models launched anonymously on developer platf...
Bridging model-based control and learned policies in long-horizon manipulation has harbored a silent disagreement: co...
Long-horizon physical-world agents must reason over distant goals while grounding decisions in reliable closed-loop b...
Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observe...
We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B paramet...