News
Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models
arXiv:2510.01304v1 Announce Type: cross Abstract: Although current large Vision-Language Models (VLMs) have advanced in multimodal...
Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning
TL;DR: A team of researchers from Stanford University, SambaNova Systems and UC Berkeley introduce ACE...
AgentCompass: Towards Reliable Evaluation of Agentic Workflows in Production
arXiv:2509.14647v1 Announce Type: cross Abstract: With the growing adoption of Large Language Models (LLMs) in...
AgentArmor: Enforcing Program Analysis on Agent Runtime Trace to Defend Against Prompt Injection
arXiv:2508.01249v1 Announce Type: cross Abstract: Large Language Model (LLM) agents offer a powerful new paradigm...
Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
arXiv:2507.16802v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit considerable promise in financial applications;...
Agent0: A Fully Autonomous AI Framework that Evolves High-Performing Agents without External Data through Multi-Step Co-Evolution
Large language models need huge human datasets, so what happens if the model must create...
Agent-based computing is outgrowing the web as we know it
AI agents are moving from passive assistants to active participants. Today, we ask them to...
Agent Learning via Early Experience
arXiv:2510.08558v2 Announce Type: replace-cross Abstract: A long-term goal of language agents is to learn and...
AfriEconQA: A Benchmark Dataset for African Economic Analysis based on World Bank Reports
arXiv:2601.15297v2 Announce Type: replace Abstract: We introduce AfriEconQA, a specialized benchmark dataset for African economic...
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
arXiv:2601.05699v1 Announce Type: new Abstract: Africa is home to over one-third of the world’s languages...
AFA-LoRA: Enabling Non-Linear Adaptations in LoRA with Activation Function Annealing
arXiv:2512.22455v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a widely adopted parameter-efficient fine-tuning (PEFT)...
AegisLLM: Scaling LLM Security Through Adaptive Multi-Agent Systems at Inference Time
The Growing Threat Landscape for LLMs LLMs are key targets for fast-evolving attacks, including prompt...
