Search: “models”

A Quantitative Approximation Framework for Flow Distillation in Diffusion Models

arXiv:2606.03820v1 Announce Type: cross Abstract: We develop a quantitative approximation framework for diffusion distillation, viewing few-step sampling as error propagation under compositions of lea

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Agents

Capability Advertisement as a Market for Lemons: A Trust Layer for Heterogeneous Agent Networks

DGX agent

arXiv:2606.03034v1 Announce Type: cross Abstract: Large language model (LLM) agents have begun to delegate work to one another. Protocols such as the Model Context Protocol (MCP) and the Agent2Agent p

agentsarxiv-cs-ai

3 Jun 2026

EURO-5K: When Does Domain Pretraining Matter? Benchmarking Transformers for EU Reporting Obligation Extraction

arXiv:2606.02971v1 Announce Type: new Abstract: Extracting reporting obligations from EU legislation is critical for assessing and reducing regulatory reporting burden. However, distinguishing reporti

Evaluating LLMs' Effectiveness on Real-World Consumer Device Repair Questions

arXiv:2606.03331v1 Announce Type: cross Abstract: Consumer device repair is an important but underexplored testbed for large language models (LLMs). Repair tasks require reasoning over incomplete prob

Fast Unlearning at Scale via Margin Self-Correction

arXiv:2606.02920v1 Announce Type: new Abstract: Language-model unlearning updates a trained model to behave as if it had not seen selected training examples, while preserving utility and avoiding cost

Gemma 4 12B is here! Dense, mid-sized Gemma that fits right on your laptop - released by @google under Apache 2.0 Available now in LM Studio…

model-releaseslm-studio--x

Gemma 4 12B is a newly released dense language model from Google available under the Apache 2.0 open license, designed for mid-sized computing resources that can run locally on personal computers. The

Safety

Inference Cost Attacks for Retrieval-Augmented Large Language Models

arXiv:2606.02643v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG)-enhanced LLM systems, while powerful, introduce substantial inference costs due to the inclusion of an extra mult

safetyarxiv-cs-ai

Introducing new capabilities to GPT-Rosalind

GPT-Rosalind is an OpenAI model with newly introduced capabilities designed to enhance its performance in specific tasks or domains. The update likely expands the model's functionality in areas such a

model-releasesopenai

Language Bias under Conflicting Information in Multilingual LLMs

arXiv:2604.07123v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been shown to contain biases in the process of integrating conflicting information when answering questions. Here

LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks

arXiv:2606.03303v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong informal mathematical reasoning but struggle to generate mechanically verifiable proofs in formal languages

PSViT: A Methodology for Structurally Pruning Spiking Vision Transformers

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent

arXiv:2606.03935v1 Announce Type: cross Abstract: The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for

Relational Linearity is a Predictor of Hallucinations

arXiv:2601.11429v2 Announce Type: replace-cross Abstract: Hallucination is a central failure mode of language models (LMs). We focus on hallucinations in response to questions like: 'Which instrument

ReLoRA: Knowledge-Reusing Adaptation for Fast Rollout of Evolving LLM Services

arXiv:2606.02606v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as continuously evolving services, where frequent base-model updates may invalidate previously

State-Coupled Volatility in Latent Dynamical Systems: Recovery Under Partial Observation

arXiv:2606.02664v1 Announce Type: cross Abstract: Latent state-space models are widely used to study partially observed dynamical systems, yet most formulations assume that process variability is inde

Testing LLM Arithmetic Reasoning Generalization with Automatic Numeric-Remapping Attacks

arXiv:2606.03606v1 Announce Type: cross Abstract: Large language models achieve strong performance on arithmetic reasoning benchmarks, and one common response to arithmetic brittleness is to delegate

v0.30.4: llama-server: fix gemma4 patch wiring (#16477)

model-releasesollama-releases

Ollama v0.30.4 is a patch release addressing a bug in the llama-server component related to incorrect parameter wiring in the Gemma 4 model implementation. This fix ensures Gemma 4 models operate corr

VistaHop: Benchmarking Multi-hop Visual Reasoning for Visual DeepSearch

arXiv:2606.03273v1 Announce Type: cross Abstract: Visual DeepSearch requires multimodal large reasoning model (MLRM) agents to answer complex visual queries by repeatedly inspecting image regions, gro

Where Do We (Not) Need Temporal Context in Low-Resource Video Task Adaptation?

arXiv:2606.03837v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) and probing enable adaptation of foundation models using only a small number of trainable parameters, making it a

Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation

arXiv:2602.08873v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isola

Applications

A Biconvex Formulation for Stable Transport of Mixture Models with a Unique Solution

arXiv:2606.02515v1 Announce Type: new Abstract: Optimal transport (OT) provides a principled framework for mapping between probability distributions. Despite extensive progress, applying OT to large-s

applicationsarxiv-cs-lg

A Pre-Training Analogue of Grokking in Language Models: Tracing Delayed Grammatical Generalization

arXiv:2606.00230v1 Announce Type: new Abstract: Grokking, the phenomenon in which neural networks generalize long after fitting their training data, has been studied in supervised settings on many epo

AgentProcessBench: Diagnosing Step-Level Process Quality in Tool-Using Agents

arXiv:2603.14465v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have evolved into tool-using agents, they remain brittle in long-horizon interactions. Unlike mathematical reason

[AINews] NVIDIA Cosmos 3, Nemotron 3 Ultra, and RTX Spark

model-releaseslatent-space

NVIDIA announced three new offerings: Cosmos 3, an advanced video generation model; Nemotron 3 Ultra, an upgraded language model; and RTX Spark, likely a tool or framework for developers. These releas

ARCA: Adapter-Residual Credit Assignment When Token Signals Degenerate

arXiv:2606.00257v1 Announce Type: cross Abstract: Token-level credit assignment for language-model reinforcement learning is usually formulated as if the policy were fully trainable, while practical L

Tutorials

Before the Model Learns the Bug:Fuzzing RLVR Verifiers

arXiv:2606.01066v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) replaces human preference labels with executable reward functions such as math answer checkers, JS

tutorialsarxiv-cs-ai

Chameleon: Style-Content Disentangled Framework for Cross-Domain Object Compositing

arXiv:2606.01079v1 Announce Type: new Abstract: Image compositing aims to seamlessly insert a foreground object into a background image, and recent advances in diffusion models have significantly enha

Collaborative and Efficient Fine-tuning: Leveraging Task Similarity

arXiv:2602.07218v2 Announce Type: replace-cross Abstract: Adaptability has been regarded as a central feature in the foundation models, enabling them to effectively acclimate to unseen downstream task

CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems

arXiv:2606.00756v1 Announce Type: new Abstract: Deploying lightweight Large Language Model (LLM) agents on edge servers can reduce latency and move agentic services closer to users, but resource-const

CultureForest: Understanding and Evaluating Cultural Norm Grounded Reasoning in LLMs

arXiv:2606.01879v1 Announce Type: new Abstract: Existing research largely reduces cultural intelligence in LLMs to a knowledge-level problem, overlooking whether models can effectively utilize their a

Easy, robust approximate message passing for planted spike models

arXiv:2606.00500v1 Announce Type: cross Abstract: We present a simple and efficient algorithm for robust approximate message passing (AMP) in the spiked matrix setting. In particular, let arepsilon be

FACT: A Simple and Efficient Framework for Active Finetuning

arXiv:2606.02079v1 Announce Type: new Abstract: The main goal of active finetuning is to improve a pretrained model's performance on a specific task or domain by finetuning it with carefully selected

Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting

arXiv:2606.01289v1 Announce Type: new Abstract: Zero-shot time series forecasting aims to predict future values for previously unseen series, requiring models to generalize temporal dynamics beyond th

From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction

arXiv:2511.12081v2 Announce Type: replace-cross Abstract: Despite massive investments in scale, deep models for click-through rate (CTR) prediction often exhibit rapidly diminishing returns -- a stark

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling

arXiv:2606.00110v1 Announce Type: new Abstract: Achieving robust generalization from limited data is a central challenge in embodied intelligence. Prevailing methods fail by regressing absolute coordi

researcharxiv-cs-cv

Safety

Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation

arXiv:2510.18439v3 Announce Type: replace Abstract: Hallucination, where models generate fluent text unsupported by visual evidence, remains a major flaw in vision-language models and is particularly

safetyarxiv-cs-cl

HakushoBench: A Japanese Chart and Table VQA Benchmark from Governmental White Papers

arXiv:2606.01132v1 Announce Type: new Abstract: Understanding chart and table images is essential for applying vision-language models (VLMs) to real-world document understanding. While English benchma

Hidden Thoughts Are Not Secret: Reasoning Trace Exposure in LLMs

arXiv:2606.00642v1 Announce Type: new Abstract: Reasoning traces have become a valuable form of learning signals for improving and transferring the capabilities of large language models. In particular

How to Correctly Report LLM-as-a-Judge Evaluations

arXiv:2511.21140v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as scalable evaluators of model responses in lieu of human annotators. However, imperfect sensiti

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

arXiv:2606.00161v1 Announce Type: cross Abstract: The detection of intrusions in IoT-based networks poses challenges that cannot be overcome using traditional machine learning methods. Perhaps the big

Safety

Isolating LLM Lexical Bias: A Curation-Free Triangulated Metric for Preference-Stage Learning

arXiv:2606.00334v1 Announce Type: cross Abstract: Various language domains have undergone remarkable changes in recent years; these shifts are largely attributed to the advent of Large Language Models

safetyarxiv-cs-ai

Logit Distillation on Manifolds: Mapping by Learning

arXiv:2606.00771v1 Announce Type: cross Abstract: A simple way to improve the performance of almost any machine learning model is not to train a single but several models with diverse algorithms which

MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

arXiv:2606.02470v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and too

PaintBench: Deterministic Evaluation of Precise Visual Editing

arXiv:2606.00188v1 Announce Type: cross Abstract: While current multimodal models are proficient at open-ended visual editing, executing precise single-answer edits remains an important obstacle. To p

Local Ai

PEACE: A Planner-Executor Agent with Constraint Enforcement for UAVs

arXiv:2606.00104v1 Announce Type: cross Abstract: Foundation models are increasingly used to drive autonomous systems, yet existing approaches either keep the model in a tight control loop, raising la

local-aiarxiv-cs-ai

ProductWebGen: Benchmarking Multimodal Product Webpage Generation

arXiv:2606.01022v1 Announce Type: cross Abstract: Crafting a product display webpage from a source product image, along with layout and visual content instructions, holds significant practical value f

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression

arXiv:2606.00494v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) and Low-Rank Adaptation (LoRA) constitute the standard pipeline for efficient Large Language Model (LLM) deployment. Ho

Prototypicality Bias Reveals Blindspots in Multimodal Evaluation Metrics

arXiv:2601.04946v3 Announce Type: replace-cross Abstract: Automatic metrics are widely used to evaluate text-to-image models, often replacing human judgment in benchmarking, model selection, and large