Papers

• What Really Controls Temporal Reasoning in Large Language Models: Tokenisation or Representation of Time? (2026)
  Gagan Bhatia et al.
  1.94
• Learn-by-Wire Training Control Governance: Bounded Autonomous Training Under Stress for Stability and Efficiency (2026)
  Anis Radianis
  1.94
• TRIAGE: Dialectical Reasoning for Explainable Risk Prediction on Irregularly Sampled Medical Time Series with LLMs (2026)
  Hyeongwon Jang et al.
  1.94
• ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from Transformer (2025)
  Lin Yueyu et al.
  1.28
• APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding (2025)
  Xinyu Yang et al.
  1.28
• Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering (2025)
  William Jurayj et al.
  1.28
• Efficient Model Selection for Time Series Forecasting via LLMs (2025)
  Wang Wei et al.
  1.28
• NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes (2025)
  Tianyang Xu et al.
  1.28
• SageAttention2++: A More Efficient Implementation of SageAttention2 (2025)
  Jintao Zhang et al.
  1.28
• What Makes for Text to 360-degree Panorama Generation with Stable Diffusion? (2025)
  Jinhong Ni et al.
  1.28
• Diagonal Batching Unlocks Parallelism in Recurrent Memory Transformers for Long Contexts (2025)
  Danil Sivtsov et al.
  1.28
• Time is Encoded in the Weights of Finetuned Language Models (2023)
  Kai Nylund et al.
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• LETS-C: Leveraging Language Embedding for Time Series Classification (2024)
  Rachneet Kaur et al.
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