| Aug 09, 2026 | The Expressive Power of Transformers with Chain of Thought |
| Aug 07, 2026 | Landscape of Thoughts — Visualizing Where LLM Reasoning Actually Goes |
| Jul 27, 2026 | Magellan — Guided MCTS for Escaping the Gravity Wells of LLM Creativity |
| Jul 27, 2026 | PriorZero — Injecting LLM Priors into MuZero-Style World Models at the MCTS Root |
| Jul 27, 2026 | SuperThoughts — Reasoning Tokens in Superposition |
| Jul 27, 2026 | Huginn — Scaling Test-Time Compute via Recurrent Depth in Latent Space |
| Jul 27, 2026 | LoopFormer — Elastic-Depth Looped Transformers via Shortcut Modulation |
| Jul 27, 2026 | Think-at-Hard — Selective Latent Iteration for Looped Reasoning Transformers |
| Jul 19, 2026 | Process Reward Agents — Online Step-Wise Steering for Knowledge-Intensive Reasoning |
| Jul 19, 2026 | Tele-Lens — How Far Ahead Do LLMs Actually Plan in Chain-of-Thought? |
| Jul 19, 2026 | Reasoning Cache — Continual Improvement Over Long Horizons via Short-Horizon RL |
| Jul 19, 2026 | Context-Folding — Scaling Long-Horizon LLM Agents via Branch-and-Fold |
| Jul 19, 2026 | T3S — Training-Trajectory-Aware Token Selection for Continual Reasoning Distillation |
| Jul 18, 2026 | BG-MCTS — Budget-Guided Tree Search for Fixed Token Budgets in LLM Reasoning |
| Jul 18, 2026 | Blend-ASC — Optimal Self-Consistency via Power-Law Sample Efficiency |
| Jul 18, 2026 | SOL — Self-Optimizing Language Models via Token-Level Efficiency Policies |
| Jul 02, 2026 | WFM-TTS — Test-Time Scaling for World Foundation Models |
| Jul 02, 2026 | Monte Carlo Tree Diffusion — System 2 Planning with Diffusion Models |
| Jun 13, 2026 | Video Prediction Policy — Predictive Visual Representations as the Policy Backbone |
| Jun 13, 2026 | DreamGen — Scaling Robot Learning by Dreaming Trajectories |
| Jun 08, 2026 | LAPA — Latent Action Pretraining from Action-Label-Free Video |
| Jun 08, 2026 | Flow Matching — The Simulation-Free Recipe Under Modern Diffusion |
| Jun 08, 2026 | DreamZero — World Action Models as Zero-shot Robot Policies |
| May 25, 2026 | Polar — Agentic RL on Any Harness at Scale |
| May 21, 2026 | AlpaServe — Statistical Multiplexing with Model Parallelism for DL Serving |
| May 18, 2026 | LeWorldModel — A 15M-Parameter JEPA That Actually Trains End-to-End from Pixels |
| May 18, 2026 | FrontierSmith — Manufacturing Open-Ended Coding Problems to Train Better Code Agents |
| May 18, 2026 | SOAR — Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability |
| May 18, 2026 | Parcae: Scaling Laws for Stable Looped Language Models |
| May 18, 2026 | Meta-Harness: End-to-End Optimization of Model Harnesses |
| Oct 27, 2025 | Mamba: Linear-Time Sequence Modeling with Selective State Spaces |
| Sep 28, 2025 | LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures |
| Sep 21, 2025 | HICRA: Hierarchical Credit Assignment for LLM Reasoning |
| Sep 21, 2025 | REFRAG: Rethinking RAG-Based Decoding |
| Dec 11, 2023 | Sliced Mutual Information for Memorization and Generalization |
| Dec 11, 2023 | When Memorizing Irrelevant Data Becomes Necessary |
| Dec 11, 2023 | Chain-of-Thought Prompting: Key Papers and Variants |
| Oct 09, 2023 | GPT-3: Language Models Are Few-Shot Learners |
| Oct 09, 2023 | GPT-2: Language Models Are Unsupervised Multitask Learners |
| Oct 09, 2023 | Auto-Regressive Next-Token Predictors Are Universal Learners |
| Sep 06, 2023 | Memorization Without Overfitting in Large Language Models |
| Sep 03, 2023 | Beyond Chain-of-Thought: Graph-of-Thought Reasoning in LLMs |
| Sep 02, 2023 | Scaling Laws for Neural Language Models |
| Aug 30, 2023 | Graph of Thought: Boosting Logical Reasoning in LLMs |
| Aug 29, 2023 | Knowledge Graph Prompting Sparks Graph of Thoughts in LLMs |
| Aug 28, 2023 | Graph of Thoughts: Solving Elaborate Problems with LLMs |
| Jul 27, 2023 | Neural Tangent Kernel: Infinite-Width Networks as Kernel Methods |
| Jul 27, 2023 | Mini-batch Optimization of Contrastive Loss |
| Jul 24, 2023 | Frequency Effects on Syntactic Rule Learning in Transformers |
| Jul 23, 2023 | Why Mask Reconstruction Pretraining Helps in Downstream Tasks |
| Jul 22, 2023 | Emergent Abilities of Large Language Models |
| Jul 18, 2023 | Contextual Representation Learning beyond Masked Language Modeling |
| Jul 17, 2023 | AMOM: Adaptive Masking over Masking (AAAI 2023) |
| Jul 16, 2023 | Mask More and Mask Later (ACL 2022) |
| Jul 15, 2023 | Calibration, Entropy Rates, and Memory in Language Models |
| Jul 13, 2023 | A Closer Look at How Fine-tuning Changes BERT |
| Jul 12, 2023 | AdaGDA: Faster Adaptive Gradient Descent Ascent for Minimax Optimization |
| Jul 11, 2023 | Masked Latent Semantic Modeling (MLSM) |
| Jul 09, 2023 | Singular Value Representation: A Graph Perspective on Neural Networks |
| Jul 07, 2023 | Blessing of Class Diversity in Pre-training |
| Jul 06, 2023 | Deriving Language Models from Masked Language Models |
| Feb 01, 2023 | Neural Collapse: Terminal Phase of Deep Network Training |
| Feb 26, 2022 | BERT: Pre-training of Deep Bidirectional Transformers |
| Feb 26, 2022 | Attention Is All You Need |