17 citations · 20 across the 23 of their papers we have counts for
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cs.AI2026
How Do Agentic LLMs Decide to Call Tools? A Tool-Call Vector Shaped by Suppression
Xijie Gong, Tingxu Han, Jiahao Zhang +5
Tool calling, invoking external tools on demand, is central to agentic LLMs, yet the mechanism that decides whether a model calls a tool or responds directly remains poorly underst…
cs.AI2026
Multi-Adapter Representation Interventions via Energy Calibration
Manjiang Yu, Hongji Li, Junwei Chen +4
Representation intervention has emerged as a promising paradigm for aligning large language models toward desired behaviors without modifying model weights. Existing methods typica…
cs.AI2024★ 3 cited
Tuning-Free Accountable Intervention for LLM Deployment -- A Metacognitive Approach
Zhen Tan, Jie Peng, Tianlong Chen +1
Large Language Models (LLMs) have catalyzed transformative advances across a spectrum of natural language processing tasks through few-shot or zero-shot prompting, bypassing the ne…