Introduces APV framework and Bayesian PIIE to evaluate and enhance LLMs' reasoning about pedagogical intent, reporting strong discrimination and r=0.958 human correlation on instructional tasks.
Af- fective multimodal agents with proactive knowledge grounding for emotionally aligned marketing dialogue.arXiv preprint arXiv:2511.21728, 2025a
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A3M integrates adaptive DRL, adversarial opponent modeling, and multi-objective rewards to cut regret 30-40% versus baselines while remaining robust to strategy shifts in repeated auctions.
EVLA combines a Unified Co-State Encoder and Electro-aware Structured Reasoning Chain with physics-guided training to produce energy-optimal driving decisions, reporting +5.6% accuracy gains over fine-tuned VLM baselines on a driving QA benchmark.
citing papers explorer
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Beyond Skepticism: Evaluating LLMs Pedagogical Intent Reasoning with the Adaptive Pedagogical Vigilance Framework
Introduces APV framework and Bayesian PIIE to evaluate and enhance LLMs' reasoning about pedagogical intent, reporting strong discrimination and r=0.958 human correlation on instructional tasks.
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A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions
A3M integrates adaptive DRL, adversarial opponent modeling, and multi-objective rewards to cut regret 30-40% versus baselines while remaining robust to strategy shifts in repeated auctions.
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EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control
EVLA combines a Unified Co-State Encoder and Electro-aware Structured Reasoning Chain with physics-guided training to produce energy-optimal driving decisions, reporting +5.6% accuracy gains over fine-tuned VLM baselines on a driving QA benchmark.