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ChEmREF: Evaluating Language Model Readiness for Chemical Emergency Response

arXiv:2511.10027v1 Announce Type: new Abstract: Emergency responders managing hazardous material HAZMAT incidents face critical, time-sensitive decisions, manually navigating extensive chemical guidelines. We investigate whether today’s language models can assist responders by rapidly and reliably understanding critical information, identifying hazards, and…

Towards an Agentic Workflow for Internet Measurement Research

arXiv:2511.10611v1 Announce Type: cross Abstract: Internet measurement research faces an accessibility crisis: complex analyses require custom integration of multiple specialized tools that demands specialized domain expertise. When network disruptions occur, operators need rapid diagnostic workflows spanning infrastructure mapping, routing analysis,…

Understanding Human-AI Trust in Education

arXiv:2506.09160v4 Announce Type: replace-cross Abstract: As AI chatbots become integrated in education, students are turning to these systems for guidance, feedback, and information. However, the anthropomorphic characteristics of these chatbots create ambiguity over whether students develop trust in them in…

Black-Box On-Policy Distillation of Large Language Models

arXiv:2511.10643v1 Announce Type: cross Abstract: Black-box distillation creates student large language models (LLMs) by learning from a proprietary teacher model’s text outputs alone, without access to its internal logits or parameters. In this work, we introduce Generative Adversarial Distillation (GAD),…

ProbLog4Fairness: A Neurosymbolic Approach to Modeling and Mitigating Bias

arXiv:2511.09768v1 Announce Type: new Abstract: Operationalizing definitions of fairness is difficult in practice, as multiple definitions can be incompatible while each being arguably desirable. Instead, it may be easier to directly describe algorithmic bias through ad-hoc assumptions specific to a…