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From the 1 of 12 linked papers with an AI index.

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12 papers

cs.AI2026

DRIFTLENS: Measuring Memory-Induced Reasoning Drift in Personalized Language Models

Xi Fang, Weijie Xu, Yingqiang Ge +3

The paper introduces DRIFTLENS, a framework for measuring how injecting user-specific memory into personalized language models changes the models' reasoning steps, and evaluates me…

eess.AS2026

DNSMOS-C: Improving End-to-end Speech Quality Models via Contrastive Learning

Xinyu Liang, Fredrik Cumlin, Victor Ungureanu +3

We introduce DNSMOS-C, a compact end-to-end speech quality assessment model that extends the DNSMOS Pro framework by integrating a MOS-guided triplet-based contrastive loss. Applie…

cs.LG2026

LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search

Nikhil Abhyankar, Sha Li, Sanchit Kabra +3

Recovering governing Ordinary Differential Equations (ODEs) from data is a central challenge in modeling dynamical systems across scientific domains. Existing approaches cast disco…

cs.AI2026

The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs

Xi Fang, Weijie Xu, Yuchong Zhang +3

When an AI assistant remembers that Sarah is a single mother working two jobs, does it interpret her stress differently than if she were a wealthy executive? As personalized AI sys…

cs.CY2026

Toward Individual Fairness Without Centralized Data: Selective Counterfactual Consistency for Vertical Federated Learning

Dawood Wasif, Chandan K. Reddy, Terrence J. Moore +1

When algorithmic decisions depend on data distributed across institutions, how can we ensure that an individual's outcome does not change arbitrarily based on a protected attribute…

cs.AI2026

Stop Comparing LLM Agents Without Disclosing the Harness

Yunbei Zhang, Janet Wang, Yingqiang Ge +3

This position paper argues that, for long-horizon tasks evaluated across models with comparable frontier capability, the agent execution harness, namely the infrastructure layer th…