Inference Optimization

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Most implemented papers archive 2025-07-28

21 shown of 21 papers with code (56 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Enhanced graph-learning schemes driven by similar distributions of motifs
  11 Jul 2022 3 repositories listed
  Guided by this, we first assume that we have a reference graph that is related to the sought graph (in the sense of having similar motif densities) and then, we exploit this relation by incorporating a similarity…
• Input Convex Neural Networks
  22 Sep 2016 3 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  We show that many existing neural network architectures can be made input-convex with a minor modification, and develop specialized optimization algorithms tailored to this setting.
• CycleBNN: Cyclic Precision Training in Binary Neural Networks
  28 Sep 2024 2 repositories listed
  This paper works on Binary Neural Networks (BNNs), a promising avenue for efficient deep learning, offering significant reductions in computational overhead and memory footprint to full precision networks.
• Patched MOA: optimizing inference for diverse software development tasks
  26 Jul 2024 2 repositories listed
  This paper introduces Patched MOA (Mixture of Agents), an inference optimization technique that significantly enhances the performance of large language models (LLMs) across diverse software development tasks.
• Representing Edge Flows on Graphs via Sparse Cell Complexes
  4 Sep 2023 2 repositories listed Syntology ran 8 of 10 samples · 2 unverified
  In this paper, we generalize this approach to cellular complexes and introduce the flow representation learning problem, i.
• Brevity is the soul of sustainability: Characterizing LLM response lengths
  10 Jun 2025 1 repository listed
  A significant portion of the energy consumed by Large Language Models (LLMs) arises from their inference processes; hence developing energy-efficient methods for inference is crucial.
• Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints
  15 Apr 2025 1 repository listed
  Large Language Models (LLMs) are indispensable in today's applications, but their inference procedure -- generating responses by processing text in segments and using a memory-heavy Key-Value (KV) cache -- demands…
• SimpleAR: Pushing the Frontier of Autoregressive Visual Generation through Pretraining, SFT, and RL
  15 Apr 2025 1 repository listed Syntology ran 2 of 11 samples · 9 unverified
  This work presents SimpleAR, a vanilla autoregressive visual generation framework without complex architecure modifications.
• The 1st Solution for 4th PVUW MeViS Challenge: Unleashing the Potential of Large Multimodal Models for Referring Video Segmentation
  7 Apr 2025 1 repository listed
  Motion expression video segmentation is designed to segment objects in accordance with the input motion expressions.
• A Survey on Inference Optimization Techniques for Mixture of Experts Models
  18 Dec 2024 1 repository listed
  This survey provides both a structured overview of existing solutions and identifies key challenges and promising research directions in MoE inference optimization.
• A Temporal Linear Network for Time Series Forecasting
  28 Oct 2024 1 repository listed
  Recent research has challenged the necessity of complex deep learning architectures for time series forecasting, demonstrating that simple linear models can often outperform sophisticated approaches.
• LLM-Rank: A Graph Theoretical Approach to Pruning Large Language Models
  17 Oct 2024 1 repository listed
  We call this pruning method MLPRank.
• LLaSA: Large Language and E-Commerce Shopping Assistant
  4 Aug 2024 1 repository listed
  Through instruction tuning on our dataset, the assistant, named LLaSA, demonstrates the potential to function as an omnipotent assistant.
• Inference Performance Optimization for Large Language Models on CPUs
  10 Jul 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Large language models (LLMs) have shown exceptional performance and vast potential across diverse tasks.
• Painterly Image Harmonization using Diffusion Model
  4 Aug 2023 1 repository listed Syntology ran 13 of 16 samples · 3 unverified
  Painterly image harmonization aims to insert photographic objects into paintings and obtain artistically coherent composite images.
• Adaptive Deep Neural Network Inference Optimization with EENet
  15 Jan 2023 1 repository listed
  Instead of having every sample go through all DNN layers during prediction, EENet learns an early exit scheduler, which can intelligently terminate the inference earlier for certain predictions, which the model has high…
• ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
  21 Dec 2021 1 repository listed
  However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem.
• A Novel 1D State Space for Efficient Music Rhythmic Analysis
  1 Nov 2021 1 repository listed
  Inferring music time structures has a broad range of applications in music production, processing and analysis.
• Easy and Efficient Transformer : Scalable Inference Solution For large NLP model
  26 Apr 2021 1 repository listed
  To fill such a gap, we introduce a scalable inference solution: Easy and Efficient Transformer (EET), including a series of transformer inference optimization at the algorithm and implementation levels.
• A General Method for Amortizing Variational Filtering
  13 Nov 2018 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We introduce the variational filtering EM algorithm, a simple, general-purpose method for performing variational inference in dynamical latent variable models using information from only past and present variables, i.
• Iterative Amortized Inference
  24 Jul 2018 1 repository listed
  The failure of these models to reach fully optimized approximate posterior estimates results in an amortization gap.

Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.