Search: “models”

An Odd Estimator for Shapley Values

arXiv:2602.01399v2 Announce Type: replace-cross Abstract: The Shapley value is a ubiquitous framework for attribution in machine learning, encompassing feature importance, data valuation, and causal i

Auto-Discovery-Bench: Diagnosing Structured State Tracking in Oracle-Guided Discovery

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DGX agent

arXiv:2502.15224v2 Announce Type: replace-cross Abstract: Interactive discovery requires agents to maintain and update structured beliefs over many rounds of feedback. Before evaluating agents in nois

model-releasesarxiv-cs-ai

1 Jun 2026

Automated Prediction of Postoperative Pancreatic Fistula Using Preoperative Computed Tomography

arXiv:2605.31539v1 Announce Type: new Abstract: Postoperative pancreatic fistula (POPF) is a serious complication after pancreatic resection, increasing morbidity, hospital stay, and healthcare costs.

Bayesian Inference with Shaped Deep Non-linear MLPs

arXiv:2605.30860v1 Announce Type: cross Abstract: A central aim of deep learning theory is to characterize how neural networks make predictions in the regime of simultaneously large model and training

Beyond Agreement: Scoring Panel-Surfaced Biomedical Entity Candidates for Curator Triage

arXiv:2605.30826v1 Announce Type: cross Abstract: Biomedical NER is deceptively simple for modern LLMs: plausible biomedical mentions are easy to surface, but corpus-convention correctness depends on

Hardware

Beyond Test-Time Memory: State-Space Optimal Control for LLM Reasoning

arXiv:2603.09221v2 Announce Type: replace Abstract: Associative memory has long underpinned the design of sequential models. Beyond recall, humans reason by projecting future states and selecting goal

hardwarearxiv-cs-lg

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation

arXiv:2605.30448v1 Announce Type: cross Abstract: Black-box LLM distillation is usually evaluated as an output-matching problem: a student is considered successful when its responses are semantically

ConTrans: Learning Text-enhanced Local-global Temporal Representations for Zero-shot Temporal Action Localization

arXiv:2605.30689v1 Announce Type: cross Abstract: Zero-shot Temporal Action Localization (ZS-TAL) aims to detect and locate previously unseen actions in untrimmed videos. However, existing approaches

De-attribute to Forget for LLM Unlearning

arXiv:2605.30919v1 Announce Type: cross Abstract: The rapid development of large language models (LLMs) has raised concerns on the use of inappropriate data for training, which has led to a growing in

Depth-Dependent Indirect Prompt Injection in Tool-Calling ReAct Agents: Injection Depth, Payload Framing, and Turn-Budget Sensitivity

arXiv:2605.30686v1 Announce Type: cross Abstract: ReAct agents that interleave chain-of-thought reasoning with tool calls are increasingly deployed for real tasks such as scheduling, file retrieval, a

DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

arXiv:2506.11653v3 Announce Type: replace-cross Abstract: Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Ant

safetyarxiv-cs-ai

Discovering Differences in Strategic Behavior Between Humans and LLMs

arXiv:2602.10324v2 Announce Type: replace Abstract: As Large Language Models (LLMs) are increasingly deployed in social and strategic scenarios, it becomes critical to understand where and why their b

Distilling LLM Feedback for Lean Theorem Proving

arXiv:2605.30861v1 Announce Type: new Abstract: Post-training for reasoning models typically combines supervised fine-tuning with reinforcement learning from verifiable rewards, most commonly with GRP

safetyarxiv-cs-ai

EchoRL: Reinforcement Learning via Rollout Echoing

arXiv:2605.31228v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards is an effective route for post-training to strengthen the reasoning capability of large language models

safetyarxiv-cs-ai

Effective Biological Representation Learning by Masking Gene Expression

arXiv:2605.31562v1 Announce Type: new Abstract: RNA sequencing produces rich and diverse datasets of gene expression, offering compelling insights into cellular state and function that have many appli

EMBGuard: Constructing Hazard-Aware Guardrails for Safe Planning in Embodied Agents

arXiv:2605.30924v1 Announce Type: new Abstract: MLLM-powered embodied agents deployed in real-world environments encounter physical hazards. However, existing approaches lack explicit mechanisms for i

Expand Neurons, Not Parameters

arXiv:2510.04500v2 Announce Type: replace Abstract: This work demonstrates how increasing the number of neurons in a network without increasing its total number of non-zero parameters improves perform

Expert Merging in Sparse Mixture of Experts with Nash Bargaining

arXiv:2510.16138v2 Announce Type: replace Abstract: Existing expert merging strategies for Sparse Mixture of Experts (SMoE) typically rely on input-dependent or input-independent averaging of expert p

From Internal Diagnosis to External Auditing: A VLM-Driven Paradigm for Data-Free Online Backdoor Defense

arXiv:2601.19448v2 Announce Type: replace Abstract: Deep Neural Networks remain inherently vulnerable to backdoor attacks. Traditional test-time defenses largely operate under the paradigm of internal

safetyarxiv-cs-lg

From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves

arXiv:2602.24210v2 Announce Type: replace-cross Abstract: Large reasoning models (LRMs) produce reasoning traces (RTs) that often contain sensitive information. These leaky thoughts are difficult to c

From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors

arXiv:2605.31042v1 Announce Type: cross Abstract: LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. In local agentic harnesses, an LLM can read and wr

HYGENE: A Diffusion-based Hypergraph Generation Method

arXiv:2408.16457v5 Announce Type: replace Abstract: Hypergraphs are powerful mathematical structures that can model complex, high-order relationships in various domains, including social networks, bio

Local Ai

Hyperspectral Image Classification using Spectral-Spatial Mixer Network

arXiv:2511.15692v2 Announce Type: replace Abstract: This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture inte

local-aiarxiv-cs-cv

Identifiable Equivariant Networks are Layerwise Equivariant

arXiv:2601.21645v2 Announce Type: replace Abstract: We investigate the relation between end-to-end equivariance and layerwise equivariance in deep neural networks. We prove the following: For a networ

Tutorials

Improving Relative Representations with Learned Anchors and Whitened Inner Products

arXiv:2605.30596v1 Announce Type: new Abstract: Independently trained neural models typically converge to incompatible latent representations, creating a fundamental barrier to highly modular AI syste

tutorialsarxiv-cs-lg

Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search

arXiv:2605.30917v1 Announce Type: cross Abstract: As large-scale visual-document corpora such as arXiv papers and enterprise PDFs continue to grow, visual-document retrieval has gained increasing atte

Intel touts 130-plus edge design wins for Series 3 and launches OpenVINO Physical AI framework

model-releasessiliconangle

Intel Corp. today announced that more than 130 design engagements for its Series 3 processor family for edge artificial intelligence and edge computing designs and also unveiled a new open-source fram

Inversion-Free Natural Gradient Descent on Riemannian Manifolds

arXiv:2604.02969v2 Announce Type: replace-cross Abstract: The natural gradient method is a central tool for statistical optimisation, but its broader application is hindered by the assumption of a Euc

Local Ai

iVGR: Internalizing Visually Grounded Reasoning for MLLMs with Reinforcement Learning

arXiv:2605.31096v1 Announce Type: new Abstract: While visually grounded Chain-of-Thought (CoT) has emerged as a promising paradigm to enhance fine-grained perception in multimodal large language model

local-aiarxiv-cs-cv

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

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

LangMap: A Human-Verified Benchmark for Hierarchical Open-Vocabulary Goal Navigation

arXiv:2602.02220v2 Announce Type: replace Abstract: Language-conditioned goal navigation (LGN) requires agents to locate user-specified targets without step-by-step guidance. However, existing benchma

Last week we revamped Liteparse to be the fastest PDF parser out there ⚡️ An underrated part of liteparse is it doesn't just give you text. …

model-releasesjerry-liu--x

Last week we revamped Liteparse to be the fastest PDF parser out there ⚡️ An underrated part of liteparse is it doesn't just give you text. It gives you bounding boxes that a coding agent can use to p

Tutorials

Learning Parametric Nitrogen Fertilizer Response Curves Using Neuro Symbolic Regression

arXiv:2605.31276v1 Announce Type: new Abstract: Accurately modeling crop response to Nitrogen (N) fertilization is a fundamental challenge in precision agriculture, as it impacts both economic returns

tutorialsarxiv-cs-lg

Learning Whom to Trust: Market-Feedback Adaptive Retrieval for Frozen LLMs in Event-Driven Financial RAG

arXiv:2605.31201v1 Announce Type: new Abstract: Financial retrieval-augmented generation (RAG) systems typically rank evidence by textual relevance, but in financial markets the useful evidence source

Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs

arXiv:2605.30501v1 Announce Type: new Abstract: Watermarking embeds statistical signatures in AI-generated text for detection and attribution. We reveal a fundamental vulnerability: when users access

researcharxiv-cs-cl

Linear Scaling Video VLMs for Long Video Understanding

arXiv:2605.31598v1 Announce Type: new Abstract: Video vision-language models (VLMs) are increasingly used in long-horizon and streaming settings, yet most video encoders still rely on spatiotemporal s

researcharxiv-cs-cv

LLMs Lean on Priors, Not Programming Language Semantics

arXiv:2510.03415v3 Announce Type: replace-cross Abstract: Recent work asks whether large language models (LLMs) condition their reasoning on explicit rules rather than statistical regularities from pr

Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode

arXiv:2605.30571v1 Announce Type: cross Abstract: Physical AI systems, including robots, autonomous vehicles, embodied agents and edge copilots, often run a different inference workload from cloud LLM

MosaicLeaks:Privacy Risks in Querying-in-the-Open for Deep Research Agents

arXiv:2605.30727v1 Announce Type: new Abstract: Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external q

NGDBench: Towards Neural Graph Data Management

arXiv:2603.05529v2 Announce Type: replace-cross Abstract: Data critical to real-world decision-making is increasingly found within organizations. Such data is heterogeneous, constantly evolving, and o

Non-Parametric Probabilistic Robustness: A Conservative Risk Estimator under Unknown Perturbation Distributions

arXiv:2511.17380v2 Announce Type: replace Abstract: Deep learning (DL) models, despite their remarkable success, remain vulnerable to small input perturbations that can cause erroneous outputs, motiva

researcharxiv-cs-cv

Hardware

Nvidia releases Cosmos3-Super-Image2Video . 64B parametres

hardwarer-stablediffusion

Cosmos3-Super-Image2Video is a 64B model for temporally coherent image-to-video generation . NVIDIA's Cosmos platform is designed to accelerate Physical AI development by enabling machines to understa

Applications

OLG++: A Semantic Extension of Obligation Logic Graph

arXiv:2507.05488v2 Announce Type: replace Abstract: We present OLG++, a semantic extension of the Obligation Logic Graph (OLG) for modeling regulatory and legal rules in municipal and interjurisdictio

applicationsarxiv-cs-ai

Omni-Supervised Motion Editing: Balancing Change and Invariance through Positive-Negative Learning

arXiv:2605.30969v1 Announce Type: new Abstract: Text-based human motion editing aims to modify existing motion sequences according to natural language instructions while maintaining the consistency of

On the regularization of Wasserstein GANs

arXiv:1709.08894v3 Announce Type: replace-cross Abstract: Since their invention, generative adversarial networks (GANs) have become a popular approach for learning to model a distribution of real (unl

PInVerify: An Offline Embodied Benchmark for Active Instance Verification

arXiv:2605.30639v1 Announce Type: cross Abstract: Embodied agents have made strong progress in navigating to target objects, but reaching the goal vicinity does not guarantee that the agent has found

Agents

Pull Requests as a Training Signal for Repo-Level Code Editing

arXiv:2602.07457v2 Announce Type: replace-cross Abstract: Repository-level code editing requires models to understand complex dependencies and execute precise multi-file modifications across a large c

agentsarxiv-cs-ai

QASM-Eval: A Dataset to Train and Evaluate LLMs on OpenQASM-3 Beyond Quantum Circuits

arXiv:2605.30358v1 Announce Type: new Abstract: Quantum computing remains in the Noisy Intermediate-Scale Quantum (NISQ) era, where the performance is highly constrained to noise. Addressing the limit