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From the 1 of 71 linked papers with an AI index.

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20242026
most citedAdaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions

6 citations · 6 across the 24 of their papers we have counts for

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cs.LG2026

PowerAtlas: Towards Electricity-Computing Co-Scheduling for Power Systems

Kaiwen Jiang, Siya Xu, Ziyue Zhu +3

PowerAtlas is an LLM‑agent framework that jointly schedules electricity supply and computing workloads in data centers, ensuring grid operational constraints and computing service…

cs.LG2026

Activation Steering Induces Emergent Misalignment: A More Comprehensive Evaluation

Qi Cao, Jian Lou, Meiting Liu +4

Activation steering has emerged as a popular inference-time technique for modulating the behavior of large language models (LLMs). By constructing a steering vector from examples o…

cs.LG2026

WINDQuant: Weight-Informed Neural Decision-Making for Global Mixed-Precision LLM Quantization

Phong Nam Huu Nguyen, Khoi M. Le, Cong-Duy T Nguyen +3

Quantization is an effective approach to reduce the memory footprint and inference cost of large language models (LLMs), yet maintaining performance in the ultra-low-bit regime rem…

cs.LG2026

Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization

Huimin Xu, Shuai Zhao, Xiaobao Wu +1

Reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning ability of large language models. However, widely used RLVR algor…

cs.LG2026

Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs

Zhiyuan Hu, Yucheng Wang, Yufei He +7

Reinforcement learning (RL) has become a central paradigm for post-training large language models (LLMs), particularly for complex reasoning tasks, yet it often suffers from explor…