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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Strongly Adaptive Online Learning Achieves Uniform Discounted Regret
    Meta
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  • Hacker News (Front Page) · EN Developer Tools
    Claude Code burns ~15–20% of your tokens on a 3-word status line
    Gist claims Claude Code spends ~15–20% of tokens on a status line
    Claude
    A Gist shared on Hacker News claims Claude Code spends roughly 15–20% of its tokens generating a three-word status line. Per the page title, it offers a Bun preload that turns agent_summary off, released under the MIT license. The measurement method is not verified here.
    Read original (Hacker News (Front Page)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    IMRouter: Imbalance-aware Temporal Pattern Routing for LLM-based Time Series Forecasting
    Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.CL (Computation and Language) · EN Multimodal
    Grounding Multimodal Reasoning with Evidence-Ablated Negatives
    Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    AgentHeal: Evaluating Goal-Preserving Resource Recovery of Web Agents under Access Barriers
    AI Agents Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    Where Position Matters: Profiling-Guided Layer-Wise RoPE Allocation in Transformers
    Embeddings Machine Learning Neural Network Retrieval-Augmented Generation (RAG) Transformer
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Event2Reward: Learning Robotic Rewards from Progress Relations
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Sparse Autoencoders as Implicit Diversification Regularisers for Cross-Sectional Cryptocurrency Returns
    Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN Inference & Efficiency
    Analyzing Condensation on Patterned Surfaces via Deep Learning
    Deep Learning Inference Neural Network Retrieval-Augmented Generation (RAG)
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  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Zero-Complement Extrapolation: Parameter Recovery and Classification in Severely Imbalanced Logistic Regression under Rank-Deficient Regimes
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Reasoning or Pattern Exploitation? Mechanistic Insights from RL-Trained Language Models
    Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    EmbodiExp: Compositional Experience Transfer for Embodied Agents
    AI Agents
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    ACAM-J-MARS: Multi-Atlas Riemannian Spectral Representations for Decoding Advanced Meditation States from fMRI
    Neural Network Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN Developer Tools
    Learning Erasing Equal-Length Relational Pattern Languages in the Limit from Positive Data over Binary Alphabets
    Reinforcement Learning
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  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    DICE: Decentralized Incentive-driven Federated Learning for Efficient & Scalable Customization of Pretrained Models in Web3
    Algorithms & Theory
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  • arXiv cs.LG (Machine Learning) · EN Agents & Tool Use
    Clean Sheets and Checkpoints: Evidence Complexity for Certifying Sequential Agent Risk
    AI Agents Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Generating Critic-Guided Synthetic Experience in Latent World Models
    Neural Network Retrieval-Augmented Generation (RAG) Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Training & Fine-tuning
    PALATE: Pretrained Autoregressive LATent Embeddings
    Deep Learning Embeddings GPT
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  • arXiv cs.CL (Computation and Language) · EN Funding & M&A
    HALO: Human-Grounded Granular Evaluation of Proactive Agents
    AI Agents Neural Network
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Tactus: Tactile & Pose Sensing Glove for Natural Dexterity Data Collection
    Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    PhysicsNeMo-Mesh: GPU-Native Meshes and Simulation Cases for Physics AI
    Machine Learning Reinforcement Learning
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  • OpenAI Blog · EN Industry Adoption
    Credit Saison achieves 954% ROI in a ChatGPT Enterprise pilot
    Credit Saison reports 954% ROI in ChatGPT Enterprise pilot
    GPT
    Credit Saison's ChatGPT Enterprise pilot delivered a 954% return on investment. OpenAI describes how leaders and employees helped turn the pilot results into companywide adoption.
    Read original (OpenAI Blog) ↗
  • Cohere Blog · EN Funding & M&A
    Who Gets to Build the Frontier for AI
    Cohere argues the democratic world needs more frontier AI builders
    Neural Network NVIDIA Reinforcement Learning
    Cohere's co-founders argue AI will become part of the operating infrastructure of economies, public services and national defence. They say who builds it, under what law and accountability shapes every adopting country's choices, so more builders are needed.
    Read original (Cohere Blog) ↗
  • Cohere Blog · EN Inference & Efficiency
    Build a Financial Research Assistant with Cohere AI on AWS
    Cohere shows how to build a financial research assistant on AWS
    Deep Learning Embeddings Quantization Retrieval-Augmented Generation (RAG) Software Engineering
    Cohere details a financial research assistant on AWS that combines Embed, Rerank and Parse with SageMaker AI, OpenSearch Serverless and Bedrock to search filings and answer with page-level citations, tuning retrieval quality, latency and cost.
    Read original (Cohere Blog) ↗
  • arXiv cs.LG (Machine Learning) · EN Infrastructure & Hardware
    Closed Gates Leak: Decomposing Adjacent-Layer Cancellation in Gated Language Models
    Machine Learning Neural Network Retrieval-Augmented Generation (RAG) Transformer
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.CL (Computation and Language) · EN New Model Releases
    HEARSAYBENCH: Can AI Navigate from Abstract Human Rights to Lived Lives?
    Embeddings Reinforcement Learning
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.CL (Computation and Language) · EN Infrastructure & Hardware
    Tracing the Influence of Retrieved Literature on Scientific Ideation in LLMs
    Machine Learning Retrieval-Augmented Generation (RAG)
    Read original (arXiv cs.CL (Computation and Language)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    When Does Closed-Loop Curriculum Adaptation Help GRPO? An Analysis on Countdown
    Deep Learning Fine-tuning Machine Learning Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN Multimodal
    BASILISC: Bayesian Alignment of Siamese-Integrated Latents for Inferring Single-cell Correspondence
    Read original (arXiv cs.LG (Machine Learning)) ↗
  • arXiv cs.LG (Machine Learning) · EN New Model Releases
    Reinforcement Learning for the Game of Balatro: A Fast Simulator and Two-Policy Training Approach
    Neural Network Reinforcement Learning
    Read original (arXiv cs.LG (Machine Learning)) ↗