…Han Luo , , Abstract Agentic abstention involves determining when an AI agent should cease interaction under uncertainty, requiring sequential decision-making across multiple environments and task types. Generated by Qwen/Qwen2.5-Coder…
…Quantization for Rate-Distortion Optimization of Generative Image Compression (2026) What Matters in Practical Learned Image Compression (2026) Dual-Latent Collaborative Decoding for Fidelity-Perception Balanced Image Compression (2026) CATRF: Codec-Adaptive…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Reinforcement Learning (RL) with verifiable environments has emerged as a powerful approach for enhancing the reasoning capabilities of Large Language Models (LLMs). While prior…
…2 # Minimum reasoning steps before code require_action_field: true # Each step must have thought + action = freedom confidence_calibration: true # Post-process confidence scores ciritcally high! Congrads! Get Pi as the agent…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct While large language models have been dominating the research landscape recently, small language models remain highly relevant across various domains; yet, they receive far…
Papers arxiv:2607.05803 Quantifying and Expanding the Theoretical Capacity of Late-Interaction Retrieval Models Published on Jul 7 Submitted by Julian Killingback on Jul 8 University of Massachusetts Amherst Authors: , , , Abstract…
…augmented generation, autonomous agents, and AI assistants. However, security remains a major concern for their widespread deployment, with threats such as prompt injection and knowledge corruption . To quantify the security risks faced…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Reinforcement Learning with Verifiable Rewards algorithms like GRPO have emerged as the dominant post-training paradigm for complex reasoning in LLMs, yet commonly suffer…
…Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting (2026) QuantWeather: Quantile-Aware Probabilistic Forecasting for Subseasonal Precipitation (2026) Please give a thumbs up to this comment if you found it…
…The quantitative results confirmed AGE's consistent performance gain in GraphRAG tasks while maintaining computational cost. We hope this work contributes to structured knowledge representation for intelligent agents and facilitates cross-modal…