arXiv AI
Jun 12
Evoflux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents
arXiv:2606. 12674v1 Announce Type: new Abstract: Compact language models (LMs) reduce cost, latency, and deployment risk for tool agents.
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 12
SAIGuard: Communication-State Simulation for Proactive Defense of LLM Multi-Agent Systems
arXiv:2606. 12474v1 Announce Type: cross Abstract: LLM-based multi-agent systems (MAS) solve complex tasks through inter-agent collaboration, but their communication-driven nature also allows security risks to spread across agents and trigger system-wide failures.
arXiv AI
Jun 12
ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages
arXiv:2606. 13572v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized settings such as healthcare, especially in multilingual and low-resource scenarios.
arXiv AI
Jun 12
LLM-Powered Personalized Glycemic Assessment in Type 2 Diabetes with Wearable Sensor Data
arXiv:2606. 12699v1 Announce Type: cross Abstract: Type 2 Diabetes (T2D) poses an increasing global health threat, demanding effective glycemic assessment to support personalized and improved diabetes care.
arXiv AI
Jun 12
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
arXiv:2606. 13177v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly expected to operate over long-term interactions, where information from past dialogues must be preserved and recalled to support future tasks.
arXiv AI
Jun 12
Position: Generative Engine Optimization Creates Underexamined Risks, Governance Must Target Concentration, Disclosure, and Academic Blind Spots
arXiv:2606. 12439v1 Announce Type: cross Abstract: Large language model (LLM) answer engines are increasingly used for information seeking, shifting visibility from ranked lists to synthesized answers.
arXiv AI
Jun 12
Representing Time Series as Structured Programs for LLM Reasoning
arXiv:2606. 12481v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong reasoning and instruction-following capabilities, making them potentially powerful tools for time-series analysis.
arXiv AI
Jun 12
One Polluted Page Is Enough: Evaluating Web Content Pollution in Generative Recommenders
arXiv:2606. 13610v1 Announce Type: cross Abstract: Search-augmented LLMs increasingly mediate everyday consumer recommendations by retrieving live web content.
arXiv AI
Jun 12
scLLM-DSC: LLM-Knowledge Enhanced Cross-Modal Deep Structural Clustering for Single-Cell RNA Sequencing
arXiv:2606. 13007v1 Announce Type: cross Abstract: Clustering is fundamental to scRNA-seq analysis, serving as a cornerstone for identifying cell populations and resolving tissue heterogeneity.
arXiv AI
Jun 12
HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection
arXiv:2606. 12620v1 Announce Type: cross Abstract: Thanks to the rapid adoption of AI code assistants powered by large language models (LLMs), industry codebases are, increasingly, a hybrid of AI- and human-authored code.
arXiv AI
Jun 12
GeoWorld-VLM: Geometry from World Models for Vision-Language Models
arXiv:2605. 16713v2 Announce Type: replace-cross Abstract: Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behind, and between.
arXiv AI
Jun 12
The Pragmatic Persona: Discovering LLM Persona through Bridging Inference
arXiv:2604. 24079v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) reveal inherent and distinctive personas through dialogue.
arXiv AI
Jun 12
Prism: Cost-Efficient Multi-LLM Serving via GPU Memory Ballooning
arXiv:2505. 04021v3 Announce Type: replace-cross Abstract: Inference providers must maintain availability for many LLMs, including low-volume but essential models, making resource efficiency increasingly important as token prices fall.
arXiv AI
Jun 12
PI-Hunter: Automated Red-Teaming for Exposing and Localizing Prompt Injections
arXiv:2606. 12737v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly evolving into agentic systems that interact with external tools and environments, introducing new security risks such as indirect prompt injection attacks through untrusted external sources.
arXiv AI
Jun 12
Neuro-Symbolic Agents for Regulated Process Automation: Challenges and Research Agenda
arXiv:2606. 13405v1 Announce Type: new Abstract: LLM-based agents are entering regulated industries where they automate judgment intensive quality management processes.
arXiv AI
Jun 12
Diffusion Transformer World-Action Model for AV Scene Prediction
arXiv:2606. 12987v1 Announce Type: cross Abstract: Action-conditioned world models let an autonomous vehicle predict future camera scenes from its own planned controls, enabling planning and simulation without real-world rollouts, but at compact, trainable scale the futures are ambiguous and the field's standard distortion metrics actively mislead: they reward a blurry regression mean over a realistic prediction.
arXiv AI
Jun 12
CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts
arXiv:2606. 13024v1 Announce Type: cross Abstract: Granger Causal Discovery (GCD) is fundamental for analyzing temporal dependencies in complex systems.
arXiv AI
Jun 12
Order Is Not Control
arXiv:2606. 12923v1 Announce Type: cross Abstract: AI alignment, interpretability, steering, and neural perturbation studies identify order-inducing objects.
arXiv AI
Jun 12
Cross-Model Disagreement as a Label-Free Correctness Signal
arXiv:2603. 25450v2 Announce Type: replace Abstract: Detecting when a language model is wrong without ground truth labels is a fundamental challenge for safe deployment.
arXiv AI
Jun 12
AfriSUD: A Dependency Treebank Collection for Evaluating Models on African Languages
arXiv:2606. 12708v1 Announce Type: cross Abstract: Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP.