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20212026
most citedExpeL: LLM Agents Are Experiential Learners

16 citations · 29 across the 25 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

SPADE: Self-Play in Adaptive Synthetic Executable Environments

Bo Liu, Simon Yu, Yiding Jiang +15

Continuous self-improvement requires an ever-expanding pool of self-generated, diverse, adaptive goals. For language agents, existing training environment pools (hand-curated, stat…

cs.CL2026

Shieldstral

Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273

We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…

cs.CL2025

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Shenzhi Wang, Le Yu, Chang Gao +15

Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful approach to enhancing the reasoning capabilities of Large Language Models (LLMs), while its mechanis…

cs.CL2024

Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models

Luhang Sun, Varsha Pendyala, Yun-Shiuan Chuang +6

This paper leverages large-language models (LLMs) to experimentally determine optimal strategies for scaling up social media content annotation for stance detection on HPV vaccine-…

cs.CL2024★ 1 cited

Scaffolded Language Models with Language Supervision for Mixed-Autonomy: A Survey

Matthieu Lin, Jenny Sheng, Andrew Zhao +7

This survey organizes the intricate literature on the design and optimization of emerging structures around post-trained LMs. We refer to this overarching structure as scaffolded L…