arXiv:2608.24188v1 Announce Type: new Abstract: Coding agents re-send large file reads and tool outputs to a frontier LLM every turn, and this context…
Category: AI
AHEAD: Adaptive Hindsight with Environment-Augmented Distillation for Agentic RL
arXiv:2608.24114v1 Announce Type: new Abstract: Training multi-turn LLM agents with reinforcement learning typically relies on trajectory-level rewards,…
NVIDIA Jetson Orin Nano 2 brings physical AI to drones and robots
NVIDIA has unveiled the Jetson Orin Nano 2, an edge robotics computer aimed at bringing physical AI to drones, robots, and vision systems. The company is…
Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping
arXiv:2608.24135v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has emerged as a pivotal technique for enhancing the…
EMRB: A Multi-Level Benchmark for Evaluating LLM Reasoning over Raw Electromagnetic Signals
arXiv:2608.24086v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as code agents for scientific and engineering analysis,…
AgentWorld: Personality-Aware Reliability Evaluation for Agentic Information Retrieval
arXiv:2608.24076v1 Announce Type: new Abstract: Evaluation of agentic information retrieval remains limited to scripted interactions with uniform users,…
Scalable Question-Centric Text-to-Image Evaluation: Reliable Ranking, Fine-Grained Diagnosis, and Cost-Aware Routing
arXiv:2608.24112v1 Announce Type: new Abstract: Modern text-to-image (T2I) models often have similar total scores but different strengths, making…
ACE: A Self-Correcting Agentic Canvas Editor for Multi-Slide Presentation Automation
arXiv:2608.24103v1 Announce Type: new Abstract: Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two…
Advancing price-performance for developers with GPT‑5.6 in Kiro
GPT‑5.6 is now available in Kiro, helping developers plan, build, review, and test software with better price-performance.
Are Android GUI Agents Robust Against Runtime Anomalies? AnTrap: Evaluating Agents in Dynamic Adversarial Environments
arXiv:2608.24099v1 Announce Type: new Abstract: GUI agents often encounter dynamic anomalies when deployed on Android devices, from unexpected pop-ups to…