arXiv AI
Jun 3
Formalizing the Binding Problem
arXiv:2606. 03976v1 Announce Type: cross Abstract: Representations of the world, arguably, contain information about features (e.
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv AI
Jun 3
Geometry-Aware Tabular Diffusion
arXiv:2606. 02607v1 Announce Type: cross Abstract: Tabular synthesis is critical for privacy-preserving sharing and augmentation, yet diffusion models rely on implicit mechanisms to capture inter-column relationships.
arXiv AI
Jun 3
Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States
arXiv:2606. 02907v1 Announce Type: cross Abstract: Linear probing of large language model (LLM) hidden states is widely used to claim that models learn distinct representations for different reasoning types.
arXiv AI
Jun 3
TriEval: A Resource-Efficient Pipeline for LLM Bias, Toxicity, and Truthfulness Assessment
arXiv:2606. 03036v1 Announce Type: new Abstract: LLMs have evolved from basic chatbots to the backbone of the AI ecosystem, now widely used in healthcare, schools, and government services.
arXiv AI
Jun 3
Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems
arXiv:2606. 02755v1 Announce Type: cross Abstract: Large language model (LLM) applications are increasingly expected to satisfy deterministic institutional requirements while relying on probabilistic generative components.
arXiv AI
Jun 3
SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents
arXiv:2605. 03353v3 Announce Type: replace-cross Abstract: LLM agents increasingly rely on reusable skills (e.
arXiv AI
Jun 3
Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor
arXiv:2605. 20402v3 Announce Type: replace-cross Abstract: MXFP4 arithmetic can dramatically accelerate reinforcement learning (RL) post-training of large language models (LLMs), yet the quantization error introduces severe accuracy degradation.
arXiv AI
Jun 3
Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories
arXiv:2606. 03979v1 Announce Type: cross Abstract: The past few decades have witnessed significant advances in the design of machine learning algorithms, from early studies on task-specific shallow models to more general deep Large Language Models (LLMs).
arXiv Machine Learning
Jun 3
Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures
arXiv:2606. 02912v1 Announce Type: cross Abstract: Forecasting seismic waveforms beyond observed data remains challenging due to the nonlinear, dispersive, and multi-scale nature of seismic wave propagation.
arXiv AI
Jun 3
DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA
arXiv:2510. 16302v2 Announce Type: replace Abstract: Multi-hop reasoning for question answering (QA) plays a critical role in retrieval-augmented generation (RAG) for modern large language models (LLMs).
arXiv AI
Jun 3
$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
arXiv:2604. 18995v2 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive generation by enabling parallel token prediction.
arXiv AI
Jun 3
CodeHacker: Automated Test Case Generation for Detecting Vulnerabilities in Competitive Programming Solutions
arXiv:2602. 20213v2 Announce Type: replace-cross Abstract: The evaluation of Large Language Models (LLMs) for code generation relies heavily on the quality and robustness of test cases.
arXiv Machine Learning
Jun 3
MuLoCo: Muon is a practical inner optimizer for DiLoCo
arXiv:2505. 23725v3 Announce Type: replace Abstract: DiLoCo is a powerful framework for training large language models (LLMs), enabling larger optimal batch sizes and increased accelerator utilization under networking constraints.
arXiv Machine Learning
Jun 3
Text-attributed Graph Condensation via Text Selection and Attribute Matching
arXiv:2606. 03839v1 Announce Type: new Abstract: Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description.
arXiv AI
Jun 3
Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation
arXiv:2602. 08873v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now used for academic expert recommendation.
arXiv AI
Jun 3
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management
arXiv:2606. 03841v1 Announce Type: new Abstract: Recent progress in Large Language Model (LLM) agents has enabled promising advances in automated data science.
arXiv AI
Jun 3
Measuring Weak-to-Strong Legibility of Reasoning Models
arXiv:2603. 20508v2 Announce Type: replace-cross Abstract: Reasoning language models (RLMs) and the intermediate chains of thought they emit play an increasingly central role in multi-agent setups such as inter-model monitoring or distillation into smaller models.
arXiv AI
Jun 3
The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models
arXiv:2606. 03645v1 Announce Type: cross Abstract: Large Language Models exhibit paradoxical fragility in fundamental arithmetic, implying a disconnect between internal computation and discrete output.
arXiv AI
Jun 3
Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis
arXiv:2606. 03566v1 Announce Type: cross Abstract: Background: The lateral ventricle choroid plexus (LVCP) is gaining recognition as a key imaging biomarker for multiple sclerosis (MS) related to physical disability and neuroinflammation.
arXiv AI
Jun 3
Cross-Lingual Token Arbitrage: Optimizing Code Agent Context Windows via Local LLM Preprocessing
arXiv:2606. 03618v1 Announce Type: new Abstract: AI-assisted coding agents are bottlenecked by input-token cost.