Increase Recommendation Systems’ Precision with LLMs, Using Python
This is how LLMs are used today to increase precision in recommendation systems
The post Increase Recommendation Systems’ Precision with LLMs, Using Python appeared first on Towards Data Science.
Xiaomi MiMo and TileRT Push a 1-Trillion-Parameter Model Past 1000 Tokens Per Second on Commodity GPUs
Xiaomi's MiMo team, with TileRT, released MiMo-V2.5-Pro-UltraSpeed, a serving mode for the MiMo-V2.5-Pro model. It decodes over 1000 tokens per second on a 1-trillion-parameter model using a single 8-GPU commodity node.
The post Xiaomi MiMo and TileRT Push a 1-Trillion-Parameter Model Past 1000 Toke...
Build an Emergency Helpline Voice Agent with LangChain
We have all been in an emergency where every second matters. Someone’s life is at risk but there you’re panicking. Now, imagine in this situation of distress when a helpline asks you to press numbers on your keypad to connect with the right agent? Pure chaos, right? Here, we just need someone to lis...
The following article originally appeared on Addy Osmani’s blog and is being reposted here with the author’s permission. A long-running AI agent can keep making progress over hours, days, or weeks. It can do this across many context windows and sandboxes, recover from failure, leave structured artif...
The Polynomial That Fixed 30 Years of Cloth Simulation
The clipping bug has lived in every 3D simulation pipeline for three decades. Here is exactly why it happens, how the math breaks, and how swapping one equation fixes it; as well as the python code to see it for yourself!
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Choosing the Right Vector Database for RAG and AI Applications
Modern AI applications rely on understanding meaning rather than matching keywords. As large language models, semantic search, and RAG systems have become mainstream, vector databases have emerged as critical infrastructure for storing and retrieving high-dimensional embeddings at scale. Choosing th...
The following article originally appeared on Paolo Perrone’s The AI Engineer Substack and is being reposted here with the author’s permission. Your team picks LangGraph for a customer support chatbot. Three weeks in, you’ve got 14 nodes in a state graph, a custom checkpointer writing to Redis, and r...
Google Research Adds Agentic RAG to Gemini Enterprise Agent Platform with a Sufficient Context Agent for multi-hop queries
Google Research details an agentic RAG framework in Gemini Enterprise Agent Platform. A Sufficient Context Agent re-searches until multi-hop, multi-source queries have enough grounding to answer. The framework raises factuality accuracy up to 34% versus standard RAG.
The post Google Research Adds Ag...
Elmes*: Automated Construction of Fine-Grained Evaluation Rubrics for Large Language Models in Long-Tail Educational Scenarios
arXiv:2606.06546v1 Announce Type: new
Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know. Existing benchmarks emphasize domain-general correctness or depend on manually designed rubrics that scale poorly to long-tail pedagogi...
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
arXiv:2606.06547v1 Announce Type: new
Abstract: Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a "stability lag" where early decisions remain fragile even after being written. We reveal that Post-Training Quantization (PTQ) error easily fl...
MacArena: Benchmarking Computer Use Agents on an Online macOS Environment
arXiv:2606.06560v1 Announce Type: new
Abstract: Computer-use agents (CUAs) operate graphical user interfaces (GUIs) through vision and control primitives, and their capabilities have advanced rapidly, driven in part by standardized online evaluation benchmarks such as OSWorld, which serve both as e...
arXiv:2606.06518v1 Announce Type: new
Abstract: Sudoku is a representative constraint satisfaction problem that requires global structural reasoning under strict discrete constraints. The existing works of solving Sudoku mainly focus on two dominant approaches, i.e., traditional heuristic and deep ...
SafeGene: Reusable Adapters for Transferable Safety Alignment
arXiv:2606.06519v1 Announce Type: new
Abstract: Open-weight LLMs are increasingly fine-tuned into customized assistants, but downstream fine-tuning can weaken safety alignment and make models more vulnerable to malicious prompts, even when the training data is not intentionally harmful. This create...
Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory
arXiv:2606.06523v1 Announce Type: new
Abstract: Equipping Large Language Models (LLMs) to execute reliable multi-step workflows has become a central challenge in artificial intelligence. Despite recent advances in LLMs' agentic capabilities, most agent systems still lack formal methods for specifyi...
CrowdMath: A Dataset of Crowdsourced Mathematical Research Discussions
arXiv:2606.06526v1 Announce Type: new
Abstract: Large language models have made substantial progress on mathematical reasoning, but existing benchmarks typically evaluate well-specified problems with final answers, step-by-step solutions, or complete proofs. They do not capture collaborative open-p...