Search: “llm”

Heterogeneous computing, which combines multiple types of GPUs and processors, is becoming standard in enterprise environments to handle diverse workloads more efficiently than traditional homogeneous

hardwarevultr

16 Apr 2026

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Safety

4/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctne…

DGX agent

4/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctness, regression safety, and minimality. Basically, get the LL

safetyai21-labs--x

15 Apr 2026

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning

arXiv:2505.17086v4 Announce Type: replace Abstract: Large Language Models (LLMs) equipped with modern Retrieval-Augmented Generation (RAG) systems often employ multi-turn interaction pipelines to inte

safetyarxiv-cs-cl

AffectAgent: Collaborative Multi-Agent Reasoning for Retrieval-Augmented Multimodal Emotion Recognition

model-releasesarxiv-cs-cv

arXiv:2604.12735v1 Announce Type: new Abstract: LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this p

Agentic Insight Generation in VSM Simulations

arXiv:2604.12421v1 Announce Type: new Abstract: Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large l

agentsarxiv-cs-cl

AISafetyBenchExplorer: A Metric-Aware Catalogue of AI Safety Benchmarks Reveals Fragmented Measurement and Weak Benchmark Governance

arXiv:2604.12875v1 Announce Type: new Abstract: The rapid expansion of large language model (LLM) safety evaluation has produced a substantial benchmark ecosystem, but not a correspondingly coherent m

b8797

Build b8797 is a sequentially numbered incremental release of llama.cpp, the open-source C/C++ library for local LLM inference maintained by ggml-org on GitHub. As part of llama.cpp's rapid, continuou

b8802

**b8802** is a numbered incremental build release of [llama.cpp](https://github.com/ggml-org/llama.cpp), an open-source C/C++ framework for running large language model (LLM) inference locally and in

b8804

Build b8804 is an automated incremental release of [llama.cpp](https://github.com/ggml-org/llama.cpp), the open-source C/C++ framework for local LLM inference. Like all llama.cpp builds, it is trigger

b8806

**b8806** is a sequential build release of [llama.cpp](https://github.com/ggml-org/llama.cpp), an open-source C/C++ framework for running large language model (LLM) inference locally. Like other numbe

b8807

**b8807** is a sequentially numbered automated build release of [llama.cpp](https://github.com/ggml-org/llama.cpp), an open-source C/C++ framework for running large language model (LLM) inference loca

Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering

arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely

researcharxiv-cs-ai

Built GPT-2, Llama 3, and DeepSeek from scratch in PyTorch - open source code + book [p]

model-releasesr-machinelearning

A Reddit post on r/MachineLearning sharing an open-source project and accompanying book by Sebastian Raschka that walks through implementing GPT-2, Llama 3, and DeepSeek from scratch using PyTorch, wi

Data Fabric: Querying agent traces in BigQuery

How to join LLM traces with billing, infrastructure, and customer data using Iceberg and BigQuery If you run AI agents in production, you’ve probably run into a simple problem: you... The post Data Fa

agentsarize-ai

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization

arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl

Large Language Models are Powerful Electronic Health Record Encoders

arXiv:2502.17403v5 Announce Type: replace-cross Abstract: Electronic Health Records (EHRs) offer considerable potential for clinical prediction, but their complexity and heterogeneity challenge tradit

Latent-Condensed Transformer for Efficient Long Context Modeling

arXiv:2604.12452v1 Announce Type: new Abstract: Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic

researcharxiv-cs-cl

LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries

arXiv:2601.10398v3 Announce Type: replace Abstract: In LLM-based text-to-SQL systems, unanswerable and underspecified user queries may generate not only incorrect text but also executable programs tha

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation

arXiv:2604.13010v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an efficient post-training paradigm for large language models. However, standard OPD requires a live teach

LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Software

arXiv:2604.12994v1 Announce Type: cross Abstract: Logical vulnerabilities in software stem from flaws in program logic rather than memory safety, which can lead to critical security failures. Although

Memory as Metabolism: A Design for Companion Knowledge Systems

arXiv:2604.12034v1 Announce Type: new Abstract: Retrieval-Augmented Generation remains the dominant pattern for giving LLMs persistent memory, but a visible cluster of personal wiki-style memory archi

No More Stale Feedback: Co-Evolving Critics for Open-World Agent Learning

arXiv:2601.06794v2 Announce Type: replace Abstract: Critique-guided reinforcement learning (RL) has emerged as a powerful paradigm for training LLM agents by augmenting sparse outcome rewards with nat

RFC: Solving the Metacognitive Deficit—A Modular Architecture for Self-Auditing and Live Weight-Correction in Agentic Systems

This Reddit post (r/ollama) proposes a community RFC (Request for Comments) discussing a modular architectural framework designed to address the 'metacognitive deficit' in agentic LLM systems — specif

agentsr-ollama

Ride the Wave: Precision-Allocated Sparse Attention for Smooth Video Generation

arXiv:2604.12219v1 Announce Type: cross Abstract: Video Diffusion Transformers have revolutionized high-fidelity video generation but suffer from the massive computational burden of self-attention. Wh

local-aiarxiv-cs-ai

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From

arXiv:2509.26404v2 Announce Type: replace-cross Abstract: Fingerprinting Large Language Models (LLMs)is essential for provenance verification and model attribution. Existing fingerprinting methods are

Applications

SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism

arXiv:2506.01979v4 Announce Type: replace-cross Abstract: Recently, speculative decoding (SD) has emerged as a promising technique to accelerate LLM inference by employing a small draft model to propo

applicationsarxiv-cs-ai

The A-R Behavioral Space: Execution-Level Profiling of Tool-Using Language Model Agents in Organizational Deployment

arXiv:2604.12116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents capable of executing system-level operations. While existing benchmarks

The Stackelberg Speaker: Optimizing Persuasive Communication in Social Deduction Games

arXiv:2510.09087v2 Announce Type: replace Abstract: Large language model (LLM) agents have shown remarkable progress in social deduction games (SDGs). However, existing approaches primarily focus on i

TimeMark: A Trustworthy Time Watermarking Framework for Exact Generation-Time Recovery from AIGC

arXiv:2604.12216v1 Announce Type: cross Abstract: The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes. Watermarkin

researcharxiv-cs-cl

Topology-Aware Reasoning over Incomplete Knowledge Graph with Graph-Based Soft Prompting

arXiv:2604.12503v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable capabilities across various tasks but remain prone to hallucinations in knowledge-intensive scenari

researcharxiv-cs-ai

Transferable Expertise for Autonomous Agents via Real-World Case-Based Learning

arXiv:2604.12717v1 Announce Type: new Abstract: LLM-based autonomous agents perform well on general reasoning tasks but still struggle to reliably use task structure, key constraints, and prior experi

When to Forget: A Memory Governance Primitive

arXiv:2604.12007v1 Announce Type: new Abstract: Agent memory systems accumulate experience but currently lack a principled operational metric for memory quality governance -- deciding which memories t

agentsarxiv-cs-ai

A Multilingual Dataset and Empirical Validation for the Mutual Reinforcement Effect in Information Extraction

arXiv:2407.10953v5 Announce Type: replace Abstract: The Mutual Reinforcement Effect (MRE) describes a phenomenon in information extraction where word-level and sentence-level tasks can mutually improv

safetyarxiv-cs-cl

Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning

model-releasesarxiv-cs-cl

arXiv:2601.03641v4 Announce Type: replace Abstract: Large Language Model (LLM)-based agents significantly extend the utility of LLMs by interacting with dynamic environments. However, enabling agents

Agentic Application in Power Grid Static Analysis: Automatic Code Generation and Error Correction

arXiv:2604.09995v1 Announce Type: cross Abstract: This paper introduces an LLM agent that automates power grid static analysis by converting natural language into MATPOWER scripts. The framework utili

Agents in Ollama and Langflow

This Reddit post from r/ollama likely discusses how to build and run AI agents locally by combining Ollama — which handles local model serving to keep data private — with Langflow's visual, drag-and-d

local-air-ollama

AI Organizations are More Effective but Less Aligned than Individual Agents

arXiv:2604.10290v1 Announce Type: new Abstract: AI is increasingly deployed in multi-agent systems; however, most research considers only the behavior of individual models. We experimentally show that

ATANT v1.1: Positioning Continuity Evaluation Against Memory, Long-Context, and Agentic-Memory Benchmarks

arXiv:2604.10981v1 Announce Type: new Abstract: ATANT v1.0 (arXiv:2604.06710) defined continuity as a system property with 7 required properties and introduced a 10-checkpoint, LLM-free evaluation met

b8783

Build b8783 is a sequential incremental release of llama.cpp, the open-source C/C++ framework for running LLM inference locally and in the cloud. As with nearby builds in the b87xx series, it likely i

b8784

Build b8784 is a tagged release of llama.cpp, the open-source C/C++ library for efficient LLM inference maintained by ggml-org on GitHub. Like other incremental builds in the project's continuous rele

b8786

Build **b8786** is an incremental release of [llama.cpp](https://github.com/ggml-org/llama.cpp), the open-source C/C++ library for local LLM inference. Like other builds in the project's continuous re

b8787

Build b8787 is a tagged release of llama.cpp, an open-source C/C++ library for running large language model (LLM) inference locally or in the cloud with minimal setup. As with all llama.cpp builds, it

b8788

Build b8788 is an incremental release of llama.cpp, the open-source C/C++ framework for efficient LLM inference developed by ggml-org. Like other builds in the project's continuous release cycle, it l

b8790

Build b8790 is an incremental automated release of llama.cpp, the open-source C/C++ library for efficient LLM inference on local hardware. Like other builds in the project's continuous release cycle,

b8791

Build b8791 is an incremental release of llama.cpp, the open-source C/C++ library for local LLM inference maintained by ggml-org on GitHub. Like other numbered builds in the project's rapid release ca

b8793

Build b8793 is a tagged release of the llama.cpp project, an open-source C/C++ framework for running large language model (LLM) inference locally or in the cloud with minimal setup. As part of llama.c

b8794

Build b8794 is an incremental release of llama.cpp, the open-source C/C++ library for running large language model (LLM) inference locally. Like other builds in the project's continuous release series

Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation

arXiv:2604.09549v1 Announce Type: cross Abstract: Recommender systems are central to online services, enabling users to navigate through massive amounts of content across various domains. However, the

agentsarxiv-cs-ai