Search: “llm”

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution

arXiv:2605.30802v1 Announce Type: cross Abstract: Prediction markets aggregate collective intelligence to forecast uncertain events, but their utility depends on reliable outcome resolution. Existing

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Tutorials

Function2Scene: 3D Indoor Scene Layout from Functional Specifications

DGX agent

arXiv:2605.30819v1 Announce Type: new Abstract: Most text-driven 3D indoor scene synthesis methods generate rooms from object-centric prompts, asking what furniture should be placed rather than how th

tutorialsarxiv-cs-cv

1 Jun 2026

G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition

arXiv:2603.10468v2 Announce Type: replace-cross Abstract: We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting,

local-aiarxiv-cs-ai

GEM-Bench: A Benchmark for Ad-Injected Response Generation within Generative Engine Marketing

model-releasesarxiv-cs-cl

arXiv:2509.14221v3 Announce Type: replace-cross Abstract: Generative Engine Marketing (GEM) is an emerging ecosystem for monetizing generative engines, such as LLM-based chatbots, by seamlessly integr

'Intelegi Romaneste?'' A Recipe for Romanian Vision-Language Models

arXiv:2605.31401v1 Announce Type: new Abstract: Vision-Language Models (VLMs) largely follow the text-only LLM trajectory, excelling on English benchmarks but sharply degrading on low-resource languag

KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware

model-releasesarxiv-cs-lg

arXiv:2603.08721v2 Announce Type: replace-cross Abstract: New AI accelerators with novel instruction set architectures (ISAs) often require developers to manually craft low-level kernels, a time-consu

Speculative Decoding Across Languages

arXiv:2605.30580v1 Announce Type: new Abstract: Speculative decoding has become a crucial component of large language model (LLM) inference, enabling faster generation by drafting multiple tokens and

The Surface You Test Is Not the Surface That Breaks

arXiv:2605.30454v1 Announce Type: cross Abstract: Tool-augmented LLM agents are vulnerable to prompt injection: a third party who controls part of the agent's context can plant instructions that the a

Tutorials

Understanding the Fundamental Design Decisions of Retrieval-Augmented Generation Systems

arXiv:2411.19463v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a critical technique for enhancing large language model (LLM) capabilities. However, pract

tutorialsarxiv-cs-ai

b9441

B9441 is a release from llama.cpp, which provides LLM inference in C/C++ . The release follows the project's versioning pattern used by the ggml-org/llama.cpp repository on GitHub, typically containin

31 May 2026

b9442

b9442 is a release of llama.cpp, an open-source LLM inference tool written in C/C++. The release likely contains updates, bug fixes, or feature improvements to the llama.cpp project. For specific deta

31 May 2026

Accelerating Constrained Decoding with Token Space Compression

arXiv:2605.29986v1 Announce Type: new Abstract: To guarantee that an LLM's outputs conform to a specified structure, context-free grammar (CFG) decoding engines force the selection of next tokens that

b9387

B9387 is a release of llama.cpp, the main playground for developing features for the GGML library, with the goal of enabling LLM inference with minimal setup and state-of-the-art performance on a wide

b9393

B9393 is a build release of llama.cpp, the C/C++ inference framework for running large language models locally. llama.cpp enables LLM inference with minimal setup and state-of-the-art performance on a

b9394

b9394 is a release of llama.cpp, a project for LLM inference in C/C++ . The release represents a specific build or version update from the ggml-org/llama.cpp repository. Without access to the specific

b9401

b9401 is a release build of llama.cpp, an LLM inference framework in C/C++ that provides tools for running large language models locally. As an intermediate build in the llama.cpp project, it includes

b9403

B9403 is an intermediate build release of llama.cpp, an open-source project enabling LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware locally and in the cl

b9406

B9406 is a release build number from the llama.cpp project, a C/C++ implementation enabling LLM inference . Based on the release numbering pattern observed in the project's history, this represents an

b9410

b9410 is a release of llama.cpp, a C/C++ project that enables LLM inference with minimal setup and state-of-the-art performance on various hardware platforms. This build identifier represents a specif

b9411

b9411 is a release version of llama.cpp, a C/C++ implementation for LLM inference . This specific release build number represents updates to the open-source project hosted on GitHub, which provides op

b9412

b9412 is a release of llama.cpp, an open-source project for LLM inference in C/C++ . Build identifier b9412 represents a specific commit or version in the llama.cpp development lifecycle, following th

Cookie-Bench: Continuous On-screen Key Interaction Evaluation for Web Generation

arXiv:2605.30000v1 Announce Type: new Abstract: Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed

CORE-T: COherent REtrieval of Tables for Text-to-SQL

arXiv:2601.13111v2 Announce Type: replace-cross Abstract: Realistic text-to-SQL workflows often require joining multiple tables. As a result, accurately retrieving the relevant set of tables becomes a

DeepTool: Scaling Interleaved Deliberation in Tool-Integrated Reasoning via Process-Supervised Reinforcement Learning

arXiv:2605.29568v1 Announce Type: new Abstract: Tool-Integrated Reasoning (TIR) extends LLM capabilities by leveraging external environments. However, existing methods lack the deliberation during seq

Diagnosing Harmful Continuation in Answer-Correct Long-CoT Training Traces

arXiv:2605.29288v1 Announce Type: new Abstract: Long chain-of-thought (CoT) traces are widely used as supervision for reasoning-oriented LLM SFT, yet answer-correct traces can still lead to markedly d

Safety

Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas

arXiv:2605.30003v1 Announce Type: cross Abstract: We study two-level autoresearch for cooperation: an outer-loop AI agent autonomously redesigns the inner-loop pipeline of an LLM policy-synthesis syst

safetyarxiv-cs-ai

Domino: Decoupling Causal Modeling from Autoregressive Drafting in Speculative Decoding

arXiv:2605.29707v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting multiple tokens and verifying them in parallel with the target model. However, its practical

Agents

Enhancing Multi-Agent Communication through Attention Steering with Context Relevance

arXiv:2605.30136v1 Announce Type: new Abstract: LLM-based multi-agent systems have demonstrated remarkable performance on complex tasks through collaborative reasoning. However, these systems tend to

agentsarxiv-cs-ai

Safety

GrepSeek: Training Search Agents for Direct Corpus Interaction

arXiv:2605.29307v1 Announce Type: cross Abstract: Large Language Model (LLM) search agents have shown strong promise for knowledge-intensive language tasks through multiple rounds of reasoning and inf

safetyarxiv-cs-ai

Safety

Inferring Code Correctness from Specification

arXiv:2605.29822v1 Announce Type: cross Abstract: Large language models (LLMs) have become integral to modern software development, enabling automated code generation at scale. However, validating the

safetyarxiv-cs-ai

love it! @ggerganov 's llama.cpp delivering!

model-releasesclem-delangue--x

love it! @ggerganov 's llama.cpp delivering! pibot is now running fully local, using parakeet for STT, qwen3-tts for TTS, and Qwen 3.6 as the local multi-modal LLM via llama.cpp. The STT and TTS infer

MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection

arXiv:2605.30288v1 Announce Type: new Abstract: Mid-training has become an important stage in modern LLM development, using large-scale curated mixtures to strengthen capabilities before final post-tr

Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content

arXiv:2605.29659v1 Announce Type: cross Abstract: Real-time safety filtering for large language model (LLM) applications requires classifiers that can detect unsafe prompts, toxic language, jailbreak

Applications

PassNet: Scaling Large Language Models for Graph Compiler Pass Generation

arXiv:2605.29357v1 Announce Type: new Abstract: Modern tensor compilers such as TorchInductor deliver substantial speedups on mainstream models, yet face a systematic performance ceiling on long-tail

applicationsarxiv-cs-ai

Redundant or Necessary? A Benchmark for Detecting Redundant Steps in Agent Trajectories

arXiv:2605.29893v1 Announce Type: new Abstract: LLM-based agents have demonstrated strong capabilities in solving complex tasks through multi-step reasoning and tool use. However, existing evaluation

Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2605.29401v1 Announce Type: new Abstract: Time-Series Foundation Models (TSFMs) excel at zero-shot unimodal forecasting using numerical data, but unlike LLMs they cannot consume multimodal, non-

Agents

RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models

arXiv:2603.18859v2 Announce Type: replace Abstract: Reinforcement learning (RL) shows promise for enhancing LLM agentic reasoning, yet sparse terminal rewards hinder fine-grained optimization. Process

agentsarxiv-cs-ai

SCOPE: Prompt Evolution for Enhancing Agent Effectiveness

arXiv:2512.15374v2 Announce Type: replace Abstract: Large Language Model (LLM) agents are increasingly deployed in environments that generate massive, dynamic contexts. However, a critical bottleneck

When RL Suppresses Its Own Vocabulary: Recovering Reasoning Diversity in Puzzle-to-Math Transfer

arXiv:2605.29190v1 Announce Type: cross Abstract: Reinforcement learning using verifiable rewards (RLVR) improves LLM reasoning, but the conditions under which it transfers across domains -- and why i

Applications

Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues

arXiv:2605.30051v1 Announce Type: new Abstract: A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students,

applicationsarxiv-cs-cl

Adaptive Cost-Efficient Evaluation for Reliable Patent Claim Generation

model-releasesarxiv-cs-cl

arXiv:2604.04295v3 Announce Type: replace Abstract: Automated patent claim validation demands low error tolerance. However, existing approaches face a rigidity-resource dilemma: lightweight encoders c

Tools

As agents use more context, input tokens have become the majority of price-equivalent token costs.

As AI agents handle increasingly complex tasks with extended context windows, the cost structure of LLM usage has shifted such that input tokens now represent the majority of price-equivalent expenses

toolscursor--x

As Anthropic launches Claude Opus 4.8, it raises $65B in new funding

model-releasessiliconangle

Anthropic PBC today introduced a new large language model, Claude Opus 4.8, that’s significantly better than its predecessor at complex coding tasks. The company announced the LLM alongside another ma

b9375

b9375 is a release of llama.cpp, a project for LLM inference in C/C++. The release likely contains bug fixes, performance improvements, or feature additions to the llama.cpp codebase. Specific details

b9378

Based on the available information about llama.cpp, b9378 is likely an intermediate build release of the llama.cpp project. llama.cpp enables LLM inference in C/C++ , and the project releases multiple

b9381

B9381 is a build/release tag for llama.cpp, a C/C++ framework for LLM inference. This release likely includes bug fixes, performance optimizations, and feature improvements to the project, which enabl

Benchmarks are Not Enough: RAMP for Runtime Assessing of Agentic Models in Production Systems

arXiv:2605.27492v1 Announce Type: cross Abstract: LLM agents are rapidly evolving from coding assistants into autonomous software engineering systems. However, existing evaluation methodologies remain

Beyond Chunk-Local Extraction: Cross-Chunk Graph Augmentation for GraphRAG

arXiv:2605.28004v1 Announce Type: new Abstract: GraphRAG extends retrieval-augmented generation by organizing corpora as explicit knowledge graphs, enabling graph-based retrieval for complex question