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cs.AI2026

Not What You Meant: Can LLMs Follow a Specified Negation Semantics?

Qiming Bao, Agnieszka Mensfelt, Michael J. Witbrock +1

Negation does not carry a uniform interpretation across domains. In legal, regulatory, and medical reasoning, the intended interpretation depends on the reading in force -- open- v…

cs.AI2026

Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision

Xianda Zheng, Huan Gao, Meng-Fen Chiang +3

Despite recent progress, the reasoning capabilities of large multimodal language models (MLLMs) remain fundamentally constrained by static supervision, where fixed prompts, rules,…

cs.AI2026

Separating Diagnosis from Control: Auditable Policy Adaptation in Agent-Based Simulations with LLM-Based Diagnostics

Shaoxin Zhong, Yuchen Su, Michael Witbrock

Mitigating elderly loneliness requires policy interventions that achieve both adaptability and auditability. Existing methods struggle to reconcile these objectives: traditional ag…

cs.AI2025

HealthSLM-Bench: Benchmarking Small Language Models for Mobile and Wearable Healthcare Monitoring

Xin Wang, Ting Dang, Xinyu Zhang +3

Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ultimately improving individuals' quality…

cs.AI2025

Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts

Xianda Zheng, Zijian Huang, Meng-Fen Chiang +4

Explicit knowledge conflicts, occurring when retrieved contexts contain contradictory information, pose a fundamental challenge for Large Language Models (LLMs) as they integrate i…

cs.AI2025

Bridging the Reasoning Gap: Small LLMs Can Plan with Generalised Strategies

Andrey Borro, Patricia J Riddle, Michael W Barley +1

Recent advancements in the reasoning skills of Large Language Models (LLMs) demonstrate an increase in the ability of LLMs to solve simple planning tasks. However, as long as the d…