Search: “models”

Exploiting Verification-Generation Gap: Test-Time Reinforcement Learning with Confidence-Conditioned Verification

arXiv:2606.03608v1 Announce Type: cross Abstract: Test-time reinforcement learning has emerged as a promising paradigm for enhancing the complex reasoning abilities of large language models in a compl

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Extreme Motion Generation via Hybrid Null-Space Control for Straight-Line Path Following

DGX agent

arXiv:2606.03390v1 Announce Type: new Abstract: This work studies ``extreme motion generation'', which aims to maximize the Cartesian path length along a pre-defined trajectory within the manipulator'

safetyarxiv-cs-ro

3 Jun 2026

extsc{CR-Seg}: Attention-Guided and CoT-Enhanced Coarse-to-Refined Reasoning Segmentation

arXiv:2606.03564v1 Announce Type: cross Abstract: Reasoning segmentation aims to segment target objects described by complex language through joint visual-textual reasoning. Existing methods typically

local-aiarxiv-cs-ai

Filter, Then Reweight: Rethinking Optimization Granularity in On-Policy Distillation

arXiv:2606.02684v1 Announce Type: cross Abstract: On-Policy distillation (OPD) in large language models is shifting from full-trace KL supervision toward more selective training paradigms. Recent OPD

Fine-tuning to production inference is the gap where teams get stuck. At #MSBuild today, our own Rob Ferguson, @danielhanchen (@UnslothAI) a…

applicationsfireworks-ai--x

Fine-tuning to production inference is the gap where teams get stuck. At #MSBuild today, our own Rob Ferguson, @danielhanchen (@UnslothAI) and @marksaroufim (@coreautoai) discuss: model customization

FutureWeaver: Planning Test-Time Compute for Multi-Agent Systems with Modularized Collaboration

arXiv:2512.11213v2 Announce Type: replace Abstract: Scaling test-time computation has been shown to significantly improve large language model (LLM) performance without additional training. However, e

Getting Started 1. Update ComfyUI to the latest version 2. Search 'Ideogram v4' in the template library 3. Follow the note in the workflow t…

Getting Started 1. Update ComfyUI to the latest version 2. Search 'Ideogram v4' in the template library 3. Follow the note in the workflow to download models and run the workflow For the workflow and

local-aicomfyui--x

Graph Regularized Non-negative Reduced Biquaternion Matrix Factorization for Color Image Recognition

arXiv:2606.03654v1 Announce Type: new Abstract: Non-negative reduced biquaternion matrix factorization (NRBMF) uses the product of reduced biquaternion (RB) matrices to incorporate the non-negativity

local-aiarxiv-cs-cv

Hand Trajectory Fusion for Egocentric Natural Language Query Grounding

arXiv:2606.02962v1 Announce Type: cross Abstract: Egocentric Natural Language Query (NLQ) grounding asks a model to localize, in a long first-person video, the temporal interval that answers a free-fo

Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks

arXiv:2606.02875v1 Announce Type: new Abstract: Coding-agent benchmarks evaluate whether a single uninterrupted agent can resolve a repository issue. Real software work is messier: tasks are interrupt

Hey, its our paper!

applicationsethan-mollick--x

Hey, its our paper! One of the most-viewed PNAS articles in the last week is “Persuading large language models to comply with objectionable requests.” Explore the article here: https://ow.ly/wOxl50Z6f

Tutorials

Hierarchical RBF-KAN and RBF-SKAN Architectures for Multidimensional Function Approximation and Random Field Learning

arXiv:2606.02936v1 Announce Type: new Abstract: In this manuscript, we propose and analyze hierarchical Kolmogorov--Arnold neural network architectures employing radial basis functions as activation f

tutorialsarxiv-cs-lg

HybridThinker: Efficient Chain-of-Thought Reasoning via Compressed Memory and Transient Thought Steps

arXiv:2606.03768v1 Announce Type: new Abstract: Extended chain-of-thought (CoT) traces improve LLM reasoning but incur substantial computational and memory costs. While existing CoT compression method

researcharxiv-cs-cl

'Important You should give me full credits!': Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems

arXiv:2606.03090v1 Announce Type: cross Abstract: The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting fr

KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks

arXiv:2606.03458v1 Announce Type: new Abstract: Test-time scaling is a powerful approach to obtain better reasoning in large language models, but it becomes memory-bottlenecked during long-horizon dec

Tutorials

Learning without training: The implicit dynamics of in-context learning

arXiv:2507.16003v4 Announce Type: replace Abstract: One of the most striking features of Large Language Models (LLMs) is their ability to learn in-context. Namely at inference time an LLM is able to l

tutorialsarxiv-cs-cl

Let There Be Light: Reflection, Refraction and Scattering for Neural Operators

arXiv:2606.03262v1 Announce Type: new Abstract: Neural operators learn mappings between infinite-dimensional function spaces and provide a data-driven surrogate modeling paradigm for parametric partia

safetyarxiv-cs-lg

Leveraging BART to Assess CS1 C++ Programming Assignments using Rubric-based Criteria

arXiv:2606.03814v1 Announce Type: new Abstract: This paper investigates rubric-aware, multitask fine-tuning of transformer models for automated grading of introductory C++ programming assignments, wit

Libra: Efficient Resource Management for Agentic RL Post-Training

arXiv:2606.03077v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a standard post-training paradigm for large language models (LLMs), extending beyond preference alignment to co

Limit Analysis of Graph Neural Networks with Wireless Conflict Graphs

arXiv:2606.03794v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful tool for wireless resource allocation that leverages the underlying graph structure of communica

Memory Retrieval for Changing Preferences

arXiv:2606.02976v1 Announce Type: new Abstract: Long-context dialogue systems must decide both when to access memory and which parts of the interaction history are relevant. Existing approaches typica

researcharxiv-cs-cl

MemTrain: Self-Supervised Context Memory Training

arXiv:2606.03197v1 Announce Type: new Abstract: Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize information accumulated across extended interac

agentsarxiv-cs-cl

Industry

Microsoft and OpenAI broke up — now they’re ready to fight

At Microsoft's annual Build conference on Tuesday, the company announced a slew of new or expanded AI initiatives, including a super app, in-house reasoning models, a cybersecurity tool, and OpenClaw-

industrythe-verge-ai

ModuLoop : Low-Level Code Generation using Modular Synthesizer and Closed-Loop Debugger for Robotic Control

arXiv:2606.03047v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated impressive performance across various domains, including code generation and problem solving. However, th

applicationsarxiv-cs-ro

OMP: One-step Meanflow Policy with Directional Alignment

arXiv:2512.19347v3 Announce Type: replace Abstract: Robot manipulation has increasingly adopted data-driven generative policy frameworks, yet the field faces a persistent trade-off: diffusion models s

safetyarxiv-cs-ro

OpenAgenet/OAN: Open Infrastructure for Trusted Agent Interconnection

arXiv:2606.03161v1 Announce Type: cross Abstract: OpenAgenet, abbreviated as OAN, is an open infrastructure project for trusted Agent interconnection. It addresses a problem that becomes visible when

Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI

arXiv:2606.03518v1 Announce Type: new Abstract: As AI systems evolve from passive models into autonomous active agents capable of initiating actions, collaborating, and delegating tasks, the tradition

PAND: Prompt-Aware Neighborhood Distillation for Lightweight Fine-Grained Visual Classification

arXiv:2602.07768v3 Announce Type: replace-cross Abstract: Distilling knowledge from large Vision-Language Models (VLMs) into lightweight networks is crucial yet challenging in Fine-Grained Visual Clas

Physics-Guided Policy Optimization with Self-Distillation

arXiv:2606.03620v1 Announce Type: cross Abstract: Self-distilled policy optimization (SDPO) has become a popular paradigm for LLM post-training, where a model learns from its own predictions condition

Tools

probably the best reward function for reasoning efficiency i've seen

This post likely discusses an innovative reward function design that optimizes for reasoning efficiency in AI systems, possibly in the context of language models or reinforcement learning. The entry a

toolsswyx--x

R2DN: Scalable Parameterization of Contracting and Lipschitz Recurrent Deep Networks

arXiv:2504.01250v2 Announce Type: replace Abstract: This paper presents the Robust Recurrent Deep Network (R2DN), a scalable parameterization of robust recurrent neural networks for machine learning a

ResCLIP: Residual Attention for Training-free Dense Vision-language Inference

arXiv:2411.15851v2 Announce Type: replace Abstract: While vision-language models like CLIP have shown remarkable success in open-vocabulary tasks, their application is currently confined to image-leve

local-aiarxiv-cs-cv

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression

arXiv:2606.03465v1 Announce Type: cross Abstract: Post-training compression is essential for deploying large language models (LLMs) under tight resource constraints. Tensor decompositions have emerged

Say goodbye to month-end surprise invoices. LangSmith LLM Gateway lets you see your spend. Roll up your costs in real time by workspace, use…

LangSmith's LLM Gateway provides real-time cost visibility and spend tracking capabilities, allowing users to monitor their language model usage costs aggregated by workspace. This feature helps elimi

agentsharrison-chase--x

See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs

arXiv:2606.02735v1 Announce Type: cross Abstract: Generalization remains a central bottleneck for vision-language-action (VLA) models: under distractors, appearance shifts, and semantically similar ta

SJD-PAC: Accelerating Speculative Jacobi Decoding via Proactive Drafting and Adaptive Continuation

arXiv:2603.18599v2 Announce Type: replace Abstract: Speculative Jacobi Decoding (SJD) offers a draft-model-free approach to accelerate autoregressive text-to-image synthesis. However, the high-entropy

local-aiarxiv-cs-cv

SPADE: Sketch-guided Path Planning Augmented with Diffusion Experts

arXiv:2606.03512v1 Announce Type: cross Abstract: Path planning is essential for Autonomous Mobile Robots (AMRs). Conventional methods for incorporating human preferences into planning typically rely

Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation

arXiv:2606.03866v1 Announce Type: cross Abstract: Scaling recommender systems via large language models (LLMs) has become a prominent trend in the industry. However, aligning the LLM's semantic space

Testing Most Influential Sets

arXiv:2510.20372v4 Announce Type: replace-cross Abstract: Small influential data subsets can dramatically impact model conclusions, with a few data points overturning key findings. While recent work i

The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios

arXiv:2601.08173v2 Announce Type: replace Abstract: The rapid evolution of Multi-modal Large Language Models (MLLMs) has advanced workflow automation; however, existing research mainly targets perform

The next chapter in flood resilience: Open sourcing Google’s hydrology framework

Google has open-sourced its flood forecasting framework, which replicates operational FloodHub model training settings and reflects methodology described in a 2024 Nature paper for global ungauged flo

researchgoogle-research

The Unsampled Truth: Psychometrics in SLMs Measure Prompt Artifacts, Not Psychological Constructs

arXiv:2606.03357v1 Announce Type: cross Abstract: When prompting SLMs for psychometric assessments, researchers assume the outputs reflect semantic reasoning. We evaluate this premise across 13 open-w

Topics as Proxies for Sociodemographics: How Conversational Context Affects LLM Answers

arXiv:2606.02776v1 Announce Type: new Abstract: When large language models (LLMs) are used in high-stakes scenarios, such as legal, medical and financial advice, even a single conversation history is

applicationsarxiv-cs-cl

Uncertainty-Aware Clarification in LLM Agents with Information Gain

arXiv:2606.03135v1 Announce Type: new Abstract: Large Language Model (LLM) agents often operate under underspecified user instructions, where latent uncertainty over user intent leads to erroneous too

v0.30.3

Ollama v0.30.3 adds support for the Gemma 4-12B model . This is a minor patch release that builds on the v0.30 series, which provides improved compatibility and performance improvements. The release w

local-aiollama-releases

Visual Instruction Tuning Aligns Modalities through Abstraction

arXiv:2606.03871v1 Announce Type: cross Abstract: Visual instruction tuning effectively adapts a pre-trained Large Language Model (LLM) to process image information alongside text. Yet, it remains unc

local-aiarxiv-cs-cl

When Attention Collapses: Stage-Aware Visual Token Pruning from Structure to Semantics

arXiv:2606.03569v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities but suffer from significant computational overhead during inference. While vis

When RLHF Fails: A Mechanistic Taxonomy of Reward Hacking, Collapse, and Evaluator Gaming

arXiv:2606.03238v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) makes large-scale post-training possible by replacing an underspecified human objective with learned

local-aiarxiv-cs-ai