TextReg mitigates prompt distributional overfitting via regularized text-space optimization, reporting up to +16.5% OOD accuracy gains over prior methods on reasoning benchmarks.
Mascot: Towards multi-agent socio- collaborative companion systems
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
UniSD unifies self-distillation components for autoregressive LLMs and its full integrated version improves base models by 5.4 points and baselines by 2.8 points across six benchmarks.
Presents CultivAgents, a relationship-centered multi-agent system for socio-culturally grounded gardening support, with a mixed-methods evaluation showing modest gains in gardener confidence and motivation.
citing papers explorer
-
TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization
TextReg mitigates prompt distributional overfitting via regularized text-space optimization, reporting up to +16.5% OOD accuracy gains over prior methods on reasoning benchmarks.
-
UniSD: Towards a Unified Self-Distillation Framework for Large Language Models
UniSD unifies self-distillation components for autoregressive LLMs and its full integrated version improves base models by 5.4 points and baselines by 2.8 points across six benchmarks.
-
CultivAgents: Cultivating Relationship-Centered Multi-Agent Systems for Personalized Gardening
Presents CultivAgents, a relationship-centered multi-agent system for socio-culturally grounded gardening support, with a mixed-methods evaluation showing modest gains in gardener confidence and motivation.