arXiv AI
Jul 9
Ad Headline Generation using Self-Critical Masked Language Model
arXiv:2607. 06818v1 Announce Type: cross Abstract: For any E-commerce website it is a nontrivial problem to build enduring advertisements that attract shoppers.
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
Jul 9
LoCA: Spatially-Aware Low-Rank Convolutional Adaptation of Vision Foundation Models
arXiv:2607. 06918v1 Announce Type: cross Abstract: Pre-trained Vision Foundation Models (VFMs) provide strong visual representations for diverse downstream tasks.
arXiv AI
Jul 9
Power and Limitations of Aggregation in Compound AI Systems
arXiv:2602. 21556v2 Announce Type: replace Abstract: When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the responses to produce a synthesized output.
arXiv Machine Learning
Jul 9
Dual Path Attribution: Efficient Attribution for SwiGLU-Transformers through Layer-Wise Target Propagation
arXiv:2603. 19742v2 Announce Type: replace Abstract: Understanding the internal mechanisms of transformer-based large language models (LLMs) is crucial for their reliable deployment and effective operation.
arXiv Machine Learning
Jul 9
Protocol Models: Scaling Decentralized Training with Communication-Efficient Model Parallelism
arXiv:2506. 01260v2 Announce Type: replace Abstract: Scaling models has led to significant advancements in deep learning, but training these models in decentralized settings remains challenging due to communication bottlenecks.
arXiv AI
Jul 9
SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care
arXiv:2601. 16529v4 Announce Type: replace Abstract: Large language models (LLMs) deployed in clinical decision support may acquiesce to patient requests for care that conflicts with evidence-based guidelines.
arXiv AI
Jul 9
When Prompts Ignore Structure: Graph-Based Attribute Reasoning for Calibrated VLMs
arXiv:2607. 07395v1 Announce Type: cross Abstract: Reliable confidence estimation remains a key limitation of test-time adaptation in vision-language models (VLMs), where prompt tuning improves zero-shot accuracy but often degrades calibration due to entropy-driven overconfidence.
arXiv AI
Jul 9
End-to-End LLM Flight Planning with RAG-based Memory and Multi-modal Coach Agent
arXiv:2607. 06964v1 Announce Type: cross Abstract: Bridging the gap between human pilot intent and autonomous flight operation is critical for real-world electric vertical takeoff and landing (eVTOL) aircraft deployment.
arXiv AI
Jul 9
Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning
arXiv:2607. 07178v1 Announce Type: cross Abstract: Recent breakthroughs of Reinforcement Learning (RL) have highlighted its potential for complex agentic Large Language Model (LLM) tasks.
arXiv Machine Learning
Jul 9
Mechanistic Interpretability for Neural Networks: Circuits, Sparse Features and Symbolic Reasoning
arXiv:2607. 07316v1 Announce Type: new Abstract: This article offers a comprehensive overview of mechanistic interpretability, an emerging field that seeks to reverse-engineer the internal algorithms of modern neural networks.
arXiv Machine Learning
Jul 9
How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization
arXiv:2607. 07678v1 Announce Type: new Abstract: Rotary Position Embeddings (RoPE) provide transformers with a fixed grid of positional frequencies, yet trained models use these frequencies highly non-uniformly.
arXiv AI
Jul 9
What Predicts Correctness in Text-to-SQL? A Selective-Prediction Study
arXiv:2607. 06799v1 Announce Type: cross Abstract: Evaluating uncertainty in AI-generated SQL queries requires estimating whether a query is correct, where correct means it executes to the same result as a human-written reference.
arXiv AI
Jul 9
Heterogeneity-Adaptive Diffusion Schrodinger Bridge for PET-Guided Whole-Body MRI Translation
arXiv:2607. 07401v1 Announce Type: cross Abstract: While whole-body multimodal medical imaging scanners have been increasingly recognized for more effective medical applications, the excessive long acquisition time in PET-MR scanning is a major obstacle in more efficient clinical practice.
arXiv AI
Jul 9
Does AI Understand Imaging? A Systematic Benchmark of Agentic AI for Computational Imaging Tasks
arXiv:2607. 07189v1 Announce Type: new Abstract: Vision-language models (VLMs) and agentic AI have shown strong performance on semantic visual tasks, but it remains unclear whether they can handle the physics and inverse problems that underlie computational imaging.
arXiv AI
Jul 9
AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
arXiv:2512. 11935v2 Announce Type: replace Abstract: Agentic AI systems increasingly connect large language models (LLMs) to external scientific tools, yet whether and when tool access improves prediction accuracy remains uncharacterized.
arXiv AI
Jul 9
Healthier LLMs: Retrieval-Augmented Generation for Public Health Question Answering
arXiv:2607. 06641v1 Announce Type: cross Abstract: Large language models (LLMs) achieve promising results on medical question answering benchmarks, yet their use in public health is constrained by hallucinations and the rapid evolution of official guidance.
arXiv Machine Learning
Jul 9
Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation
arXiv:2601. 14590v3 Announce Type: replace Abstract: Counterfactual explanations (CFEs) provide human-centric interpretability by identifying the minimal, actionable changes required to alter a machine learning model's prediction.
arXiv AI
Jul 9
Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass
arXiv:2607. 07696v1 Announce Type: cross Abstract: Analytical workloads operating on data stored in external database systems face a fundamental bottleneck: data access is guarded entirely by the database driver, like JDBC or ODBC, forcing all reads through query execution and other driver layers that are not designed for bulk columnar analytics.
arXiv AI
Jul 9
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
arXiv:2607. 07508v1 Announce Type: cross Abstract: Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs).
arXiv Machine Learning
Jul 9
Geometric Self-Distillation for Reasoning Generalization
arXiv:2607. 06855v1 Announce Type: new Abstract: On-policy distillation is a practical post-training recipe for large language models, supplying dense teacher supervision on the student's own trajectories.