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FLEx: Language Modeling with Few-shot Language Explanations
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Fine-tuning Small Language Models as Efficient Enterprise Search Relevance Labelers
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Fast-weight Product Key Memory
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Exploration v.s. Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
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Excess Description Length of Learning Generalizable Predictors
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EvoRoute: Experience-Driven Self-Routing LLM Agent Systems
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EvoClaw: Evaluating AI Agents on Continuous Software Evolution
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Evaluating Parameter Efficient Methods for RLVR
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Epistemological Fault Lines Between Human and Artificial Intelligence
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Enhancing LLM Planning Capabilities through Intrinsic Self-Critique
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End-to-End Test-Time Training for Long Context
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Emergent Introspective Awareness in Large Language Models
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ELLA: Efficient Lifelong Learning for Adapters in Large Language Models
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Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models
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Deep Delta Learning
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Decide Then Retrieve: A Training-Free Framework with Uncertainty-Guided Triggering and Dual-Path Retrieval
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DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
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CRoPE: Efficient Parametrization of Rotary Positional Embedding
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Context-Free Recognition with Transformers
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CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling
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CogMem: A Cognitive Memory Architecture for Sustained Multi-Turn Reasoning in Large Language Models
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CogFlow: Bridging Perception and Reasoning through Knowledge Internalization for Visual Mathematical Problem Solving
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Citation-Grounded Code Comprehension: Preventing LLM Hallucination Through Hybrid Retrieval and Graph-Augmented Context
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CaveAgent: Transforming LLMs into Stateful Runtime Operators
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Can LLMs Track Their Output Length? A Dynamic Feedback Mechanism for Precise Length Regulation
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Broken Words, Broken Performance: Effect of Tokenization on Performance of LLMs
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Beyond the Black Box: Theory and Mechanism of Large Language Models
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Beyond Gemini-3-Pro: Revisiting LLM Routing and Aggregation at Scale
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Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction
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An Information Theoretic Perspective on Agentic System Design
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An Information-Theoretic Framework for Robust Large Language Model Editing
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An Empirical Study on Noisy Data and LLM Pretraining Loss Divergence
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An Empirical Study of SFT-DPO Interaction and Parameterization in Small Language Models
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AI Meets Brain: Memory Systems from Cognitive Neuroscience to Autonomous Agents
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AI Agent Systems: Architectures, Applications, and Evaluation
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Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents
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Adaptation of Agentic AI
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Accurate Table Question Answering with Accessible LLMs
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Accelerate Speculative Decoding with Sparse Computation in Verification
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A Unified Definition of Hallucination, Or: It's the World Model, Stupid
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A Survey of Weight Space Learning: Understanding, Representation, and Generation
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A Survey of Reasoning in Autonomous Driving Systems: Open Challenges and Emerging Paradigms
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A Subgoal-driven Framework for Improving Long-Horizon LLM Agents
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A model of errors in transformers
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A Component-Based Survey of Interactions between Large Language Models and Multi-Armed Bandits
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A Comedy of Estimators: On KL Regularization in RL Training of LLMs
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Zero-Shot Performance Prediction for Probabilistic Scaling Laws
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xLLM Technical Report
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WizardCoder: Empowering Code Large Language Models with Evol-Instruct
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Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention