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20232026
most citedDR-Encoder: Encode Low-rank Gradients with Random Prior for Large Language Models Differentially Privately

4 citations · 11 across the 34 of their papers we have counts for

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cs.AI2026

Beyond Outcome Gaps: Process-Aware Fairness Diagnosis for LLM-based Multi-Agent Decision Systems

Yiran Zhao, Lu Zhou, Liming Fang +4

LLM-based multi-agent systems (MAS) are increasingly considered for high-stakes decision-making, yet outcome-based fairness audits can miss where risks arise within the decision tr…

cs.AI2026

LEAP: Likelihood Elicitation and Aggregation for LLM-based Probabilistic Forecasting

Yufei Chen, Yiran Zhao, Xiaogang Xu +3

LLM-based forecasting systems have improved on real-world tasks such as financial markets and sports outcomes, largely through stronger search and tool use. Many systems still ask…

cs.AI2026

LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications

Xiaogang Xu, Jiaqi Tang, Jianmin Chen +12

Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tools, and iterative prediction.…

cs.AI2026

ARAC: Benchmarking Auto-Research's Alignment and Completeness on End-to-End Researchs

Jiale Cui, Yueyao Yuan, Kaixi Zhong +3

The rapid advancement of Auto-Research has surfaced a fundamental evaluation challenge: how can we measure the alignment, logical coherence, and evolutionary completeness of its re…

cs.AI2026

Fair in Mind, Fair in Action? A Synchronous Benchmark for Understanding and Generation in UMLLMs

Yiran Zhao, Lu Zhou, Xiaogang Xu +3

As artificial intelligence (AI) is increasingly deployed across domains, ensuring fairness has become a core challenge. However, the field faces a "Tower of Babel'' dilemma: fairne…