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cs.CL2026

DecisionRobust: Benchmarking Robustness for JEV Style Decision Models Across Text and Vision

Yifan Lan, Zhongye Liu, Yurui Chang +4

Emerging decision models such as JEV provide typed interfaces that map task instructions and observations directly to choices, judgments, and scores. As these models are increasing…

cs.CL2026

From Narrative to Auditable Forecasts: A Structured Scaffold for Agentic Forecasting

Yuanpu Cao, Yongkang Du, Yurui Chang +2

LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events. However, current agentic forec…

cs.AI2026

Critic Experience Bank: Self-Evolving Step-Level Confidence Estimation for LLM Agents

Yaopei Zeng, Congchao Wang, JianHang Chen +3

LLM agents operate in stateful environments, where a single erroneous step can waste limited interaction budget or cause irreversible effects before task failure becomes apparent.…

cs.AI2026

Forced Deferral: Manipulating Routing Decisions in Multimodal LLM Cascades

Zhongye Liu, Yaopei Zeng, Yurui Chang +1

While multimodal large language models (MLLMs) have shown strong visual reasoning abilities, serving a large model for every query is computationally expensive. MLLM cascades mitig…

cs.LG2026

ForecastCompass: Guiding Agentic Forecasting with Adaptive Factor Memory

Yurui Chang, Yongkang Du, Yuanpu Cao +2

Agentic forecasting is important for decision-making in dynamic environments, but it remains challenging because agents must reason from incomplete, time-limited evidence and produ…

cs.LG2026

Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks

Bohan Wang, Zewen Liu, Lu Lin +4

Interpretable time series deep learning systems are often assessed by checking temporal consistency on explanations, implicitly treating this as evidence of robustness. We show tha…