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arxiv.org arXiv
arxiv.org › abs › 2312.08935v3
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
In this paper, we present an innovative process-oriented math process reward model called \textbf{Math-Shepherd}, which assigns a reward score to each step of math problem solutions. The training of M...
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arxiv.org arXiv
arxiv.org › abs › 2406.18629v1
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Mathematical reasoning presents a significant challenge for Large Language Models (LLMs) due to the extensive and precise chain of reasoning required for accuracy. Ensuring the correctness of each rea...
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arxiv.org arXiv
arxiv.org › abs › 2602.10604v2
Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters
We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most when building agents: ...
arxiv.org arXiv
arxiv.org › abs › 1708.00023v2
Two-step approach to scheduling quantum circuits
As the effort to scale up existing quantum hardware proceeds, it becomes necessary to schedule quantum gates in a way that minimizes the number of operations. There are three constraints that have to ...
arxiv.org arXiv
arxiv.org › abs › 2502.08941v3
Analysis of Off-Policy $n$-Step TD-Learning with Linear Function Approximation
This paper analyzes multi-step temporal difference (TD)-learning algorithms within the ``deadly triad'' scenario, characterized by linear function approximation, off-policy learning, and bootstrapping...
arxiv.org arXiv
arxiv.org › abs › 2507.16632v3
Step-Audio 2 Technical Report
This paper presents Step-Audio 2, an end-to-end multi-modal large language model designed for industry-strength audio understanding and speech conversation. By integrating a latent audio encoder and r...
arxiv.org arXiv
arxiv.org › abs › 2511.18834v1
FlowSteer: Guiding Few-Step Image Synthesis with Authentic Trajectories
With the success of flow matching in visual generation, sampling efficiency remains a critical bottleneck for its practical application. Among flow models' accelerating methods, ReFlow has been someho...
arxiv.org arXiv
arxiv.org › abs › 1006.1735v1
Algebraic Attack on the Alternating Step(r,s)Generator
The Alternating Step(r,s) Generator, ASG(r,s), is a clock-controlled sequence generator which is recently proposed by A. Kanso. It consists of three registers of length l, m and n bits. The first regi...
arxiv.org arXiv
arxiv.org › abs › 1608.00613v2
Skipping Selected Steps of DWT Computation in Lossless JPEG 2000 for Improved Bitrates
In order to improve bitrates of lossless JPEG 2000, we propose to modify the discrete wavelet transform (DWT) by skipping selected steps of its computation. We employ a heuristic to construct the skip...
arxiv.org arXiv
arxiv.org › abs › 2402.16396v2
Step-reinforced random walks and one-half
Under suitable moment assumptions, we show that a genuinely d-dimensional step-reinforced random walk undergoes a phase transition between recurrence and transience in dimensions $d=1,2$, and that it ...