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News
Anthropic Adds Plugin Evals to Claude Code: 6 Grader Types, a No-Plugin Baseline, and a CI Gate for Skills
1+ day, 10+ hour ago (308+ words) Deployable: Yes. It runs on Claude Code v2.1.269 or later against any directory with a plugin.json or.claude-plugin/plugin.json manifest, or a skills-directory plugin. Every eval run and judge grader is a real model call billed to your plan…...
Create a Reasoning-Focused LLM: A Practical Guide to Streaming, Curating, and Fine-Tuning the SupraLabs Reasoning Corpus
4+ week, 2+ day ago (554+ words) MarkTechPost In this tutorial, we build an end-to-end workflow for working with the SupraLabs reasoning corpus. We stream a representative subset directly from the Hugging Face Hub, inspect its source distribution, token-length patterns, task composition, and reasoning-to-answer ratios, and then…...
Stanford Researchers Introduce TRACE: A Capability-Targeted Agentic Training System That Turns Recurrent Agent Failures Into Synthetic RL Environment
1+ mon, 4+ week ago (676+ words) Agentic LLMs often fail the same way, again and again. A Stanford research team traced this to missing, reusable capabilities. Their system, TRACE, diagnoses those gaps and trains for them directly. TRACE stands for Turning Recurrent Agent failures into Capability-targeted…...
MEMO: A Modular Framework for Training a Dedicated Memory Model on New Knowledge Without Modifying LLM Parameters
3+ mon, 2+ week ago (876+ words) Large language models become static after pretraining. Their knowledge does not update as the world changes. Retraining a full LLM is too expensive at modern scales. Fine-tuning risks degrading previously learned knowledge. Retrieval-augmented generation (RAG) struggles when answers require reasoning…...
Build a Reinforcement Learning Powered Agent that Learns to Retrieve Relevant Long-Term Memories for Accurate LLM Question Answering
4+ mon, 2+ week ago (271+ words) We construct a synthetic long-term memory bank that simulates stored knowledge across multiple domains. We generate structured memory items and convert them into textual memories that can later be embedded for semantic retrieval. We also create query datasets from these…...
Meet SymTorch: A PyTorch Library that Translates Deep Learning Models into Human-Readable Equations
6+ mon, 1+ week ago (223+ words) SymTorch simplifies the engineering required to extract symbolic equations from trained models by automating data movement and hook management. The library interfaces with PySR, which uses a multi-population genetic algorithm to find equations that balance accuracy and complexity on a…...
Kyutai Releases Hibiki-Zero: A3B Parameter Simultaneous Speech-to-Speech Translation Model Using GRPO Reinforcement Learning Without Any Word-Level Aligned Data
6+ mon, 3+ week ago (254+ words) Traditional approaches rely on supervised training with word-level alignments. These alignments are difficult to collect at scale. Developers usually depend on synthetic alignments and language-specific heuristics. Hibiki-Zero removes this complexity by using a novel reinforcement learning (RL) strategy to optimize…...
A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data
7+ mon, 1+ week ago (268+ words) We set up the environment by installing dependencies, importing libraries, and fixing random seeds for reproducibility. We detect and configure the computation device to ensure consistent execution across systems. We also define a utility to create configuration objects safely across…...
A Coding and Experimental Analysis of Decentralized Federated Learning with Gossip Protocols and Differential Privacy
7+ mon, 1+ week ago (315+ words) We set up the execution environment and installed all required dependencies. We initialize random seeds and device settings to maintain reproducibility across experiments. We also load the MNIST dataset, which serves as a lightweight yet effective benchmark for federated learning…...
Meet SETA: Open Source Training Reinforcement Learning Environments for Terminal Agents with 400 Tasks and CAMEL Toolkit
8+ mon, 1+ day ago (176+ words) The SETA code repository showcases a Terminal Toolkit that turns a language model into an executable terminal agent. For each task run, the framework creates a structured log directory under evaluation/terminal_bench_run. The README page shows a concrete layout for a…...