Together AI has released DeepSWE, a state-of-the-art, fully open-sourced software engineering agent that is trained entirely through reinforcement learning (RL). […]
Category: Staff
Shanghai Jiao Tong Researchers Propose OctoThinker for Reinforcement Learning-Scalable LLM Development
Introduction: Reinforcement Learning Progress through Chain-of-Thought Prompting LLMs have shown excellent progress in complex reasoning tasks through CoT prompting combined […]
ReasonFlux-PRM: A Trajectory-Aware Reward Model Enhancing Chain-of-Thought Reasoning in LLMs
Understanding the Role of Chain-of-Thought in LLMs Large language models are increasingly being used to solve complex tasks such as […]
Baidu Researchers Propose AI Search Paradigm: A Multi-Agent Framework for Smarter Information Retrieval
The Need for Cognitive and Adaptive Search Engines Modern search systems are evolving rapidly as the demand for context-aware, adaptive […]
Baidu Open Sources ERNIE 4.5: LLM Series Scaling from 0.3B to 424B Parameters
Baidu has officially open-sourced its latest ERNIE 4.5 series, a powerful family of foundation models designed for enhanced language understanding, […]
OMEGA: A Structured Math Benchmark to Probe the Reasoning Limits of LLMs
Introduction to Generalization in Mathematical Reasoning Large-scale language models with long CoT reasoning, such as DeepSeek-R1, have shown good results […]
TabArena: Benchmarking Tabular Machine Learning with Reproducibility and Ensembling at Scale
Understanding the Importance of Benchmarking in Tabular ML Machine learning on tabular data focuses on building models that learn patterns […]
LongWriter-Zero: A Reinforcement Learning Framework for Ultra-Long Text Generation Without Synthetic Data
Introduction to Ultra-Long Text Generation Challenges Generating ultra-long texts that span thousands of words is becoming increasingly important for real-world […]
MDM-Prime: A generalized Masked Diffusion Models (MDMs) Framework that Enables Partially Unmasked Tokens during Sampling
Introduction to MDMs and Their Inefficiencies Masked Diffusion Models (MDMs) are powerful tools for generating discrete data, such as text […]
University of Michigan Researchers Propose G-ACT: A Scalable Machine Learning Framework to Steer Programming Language Bias in LLMs
LLMs and the Need for Scientific Code Control LLMs have rapidly evolved into complex natural language processors, enabling the development […]