arxiv arXiv cs.AI · 9d ago

Embedded ML Workflow for Microcontroller Edge Devices

This paper outlines a systems-oriented workflow for embedded machine learning on microcontroller-class devices. It details key engineering decisions such as data sampling, feature extraction, class imbalance validation, model-runtime co-design, and streaming deployment, using inertial motion recognition and keyword spotting as case studies. The work provides practical design rules for robust on-device inference, including data curation, quantization, thresholding, scheduling, and field monitoring.

arxiv arXiv cs.AI · 9d ago

Oracle Signals in Agent-Authored Test Code

An empirical study of 86,156 test-file patches from 33,596 agent-authored PRs reveals that 80.2% of test patches contain weak or no explicit oracle signals. Strong-oracle test files significantly improve merge likelihood (OR = 1.28, p < 0.001) after adjusting for multiple factors, indicating test file presence alone overestimates verification strength.

arxiv arXiv cs.AI · 9d ago

ReproRepo: Scaling Reproducibility Audits with GitHub Issues

ReproRepo introduces a scalable framework using GitHub issues to evaluate ML paper reproducibility. It shows that LLM agents like Codex with GPT-5.5 identify at least one blocker in 90% of paper-repository pairs without executing code, though exact localization remains challenging.

arxiv arXiv cs.CL · 9d ago

SwiftTrans Improves LLM Code Translation Efficiency

SwiftTrans addresses runtime efficiency gaps in LLM-based code translation by introducing Multi-Perspective Exploration and Difference-Aware Selection. The framework extends CodeNet, F2SBench, and introduces SwiftBench to evaluate runtime performance, showing consistent improvements in both correctness and efficiency across benchmarks.

arxiv arXiv cs.CL · 9d ago

Coding Benchmarks Misaligned with Agentic Software Engineering

Current coding benchmarks were designed before agentic software engineering and fail to capture the complexity of real-world systems. They conflate model performance with the entire harness, ignore valid alternative solutions, and lack feedback signals at individual component levels, making iterative improvement difficult.

arxiv arXiv cs.CL · 9d ago

GameCraft-Bench: Evaluating End-to-End Game Generation

GameCraft-Bench introduces a benchmark with 140 Godot tasks across 15 game families to assess coding agents' ability to generate playable games. Evaluations show the best agent achieves only 41.46% success, indicating significant challenges in producing complete, interactive games with coherent gameplay and visual feedback.

arxiv arXiv cs.CL · 9d ago

Fine-tuning LLMs for Passive Depression Severity Estimation

A model fine-tuned on Qwen3.5-27B predicts PHQ-9 scores from AI dialogue transcripts, achieving MAE=2.6 and AUC=0.91 at the PHQ-9 >= 10 threshold. It maintains AUC > 0.87 across all PHQ-9 severity levels, demonstrating accurate depression severity estimation in real-world conversations without self-reporting.

arxiv arXiv cs.CL · 9d ago

VoidPadding: Decoupling [EOS] Termination and Padding in MDLMs

VoidPadding introduces [VOID] as a padding token to separate semantic termination and response-length modeling. It improves performance on mathematical reasoning and code generation by 17.84 points over the original model and reduces decoding NFE by 55.7% on average.

media r/LocalLLaMA · 9d ago

I didn't know it was possible to compile llamacpp to run CUDA + Vulkan at the same time

A user compiled llamacpp with both CUDA and Vulkan support to leverage two GPUs, the w7800 and another card. The setup achieved +10% tokens/sec in decoding for a MiniMax-M3-UD-IQ2_M-00001-of-00004.gguf model, with plans to run benchmarks to assess real performance gains.

media r/LocalLLaMA · 9d ago

Minimax M3 (4-bit MLX) Initial Benchmark on Mac Studio M3 with 512GB

The Minimax M3 (4-bit MLX) was benchmarked on a Mac Studio M3 with 512GB storage. Results show token throughput and latency metrics across different prompt sizes, with peak performance at 269.1 tok/s for 8192-token prompts and 172.8 tok/s for a 65k-token prompt, using 228GB of peak memory.

media r/LocalLLaMA · 9d ago

GLM-5.2 Releases Open Weights with Strong Coding Performance

GLM-5.2 has launched with open weights, a 1M context window, MIT license, and two reasoning modes. Early results show it ranks near the top in coding benchmarks, indicating strong real-world potential beyond API-only models.

media r/LocalLLaMA · 9d ago

Cheapest hardware for Qwen 3.6: 27B and 35B-A3B models

A Reddit post discusses the cost-effective hardware setup for running Qwen 3.6 models, both 27B and 35B-A3B, noting that RTX 3090 24GB offers better long-term value over Tesla V100 due to discontinuation and upcoming Chinese alternatives. The proposed build totals $1,995.65, including a Ryzen 5 5600X, RTX 3090 24GB, and essential components, with the total price being a key concern for users seeking affordability.

media r/LocalLLaMA · 10d ago

Hashicorp founder claims local models aren't good enough yet

Hashicorp founder Mitchell Hashimoto states that local language models aren't good enough yet. A Reddit user disputes this, noting that over a year, many people have successfully used local models for coding, with only 'vibecoders' facing challenges.

lab Claude Code Releases · 10d ago

Claude v2.1.178 Release Notes

Claude v2.1.178 introduces new permission rules using Tool(param:value) syntax, improved workflow and skill loading in nested directories, and enhanced auto mode and error messaging. It fixes critical issues including crashes, authentication errors, and UI behavior in Chrome and VSCode, while refining tool prompts and undo functionality.

media r/LocalLLaMA · 10d ago

Community model build thread: Crowdsourced training feasible

A community model can be built through crowdsourced compute using a 'Branch-Train-Stitch' approach. Participants train a prototype model on their hardware, submit narrow-domain submodels, and organizers stitch them into a large Mixture-of-Experts (MoE) model, with key decisions including prototype size, scope definitions, and training protocols.

media r/LocalLLaMA · 10d ago

Glimmer 1: A 10,000-parameter foundational language model

Glimmer 1 is a 10,000-parameter language model trained on 500K tokens from FineWeb-Edu. It features a 512-token context window, a standard Llama architecture with 16 hidden dimensions, 2 layers, 4 attention heads, and 1 KV head using GQA, and is available on Hugging Face.

media r/LocalLLaMA · 10d ago

Anyone running Qwen 3.6 27b UD Q8 on multiple GPUs?

A user asks if anyone has successfully run Qwen 3.6 27b UD Q8 on multiple GPUs, noting issues with llamacpp and vllm. The model crashes or hangs during multi-turn requests, with llamacpp showing CUDA errors and vllm failing mid-turn, despite working well with Q5 quantization.

blog Simon Willison · 10d ago

Georgi Gerganov praises Qwen3.6-27B for coding tasks

Georgi Gerganov confirms that Qwen3.6-27B is highly capable for coding tasks, noting its daily use on local hardware like M2 Ultra and RTX 5090. He describes using a minimal pi agent with a short system prompt to align it with his workflow, highlighting its utility for maintaining open-source projects.

media r/LocalLLaMA · 10d ago

VibeThinker-3B achieves frontier math and coding performance

VibeThinker-3B, scaled from a 1.5B model, reaches frontier-level performance in math and coding tasks. It scores 94.3 on AIME'26, 80.2 on LiveCodeBench v6, 76.4 on IMO-AnswerBench, and 93.4 on IFEval, with 96.1% success on first-attempt LeetCode problems.

github llama.cpp · 10d ago

llama.cpp releases b96669 with backend sampling for Eagle3

llama.cpp version b9669 adds backend sampling support for Eagle3. The release includes binaries for macOS, Linux, Android, Windows, and openEuler across multiple architectures and hardware acceleration options, including Vulkan, CUDA, ROCm, OpenVINO, and SYCL.