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GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

arXiv:2603.12275v1 Announce Type: cross Abstract: Unlearning knowledge is a pressing and challenging task in Large Language Models (LLMs) because of their unprecedented capability to memorize and dige

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Model Releases

Google announces Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and vibe-coding own Android widgets (Allison Johnson/The Verge)

DGX agent

Allison Johnson / The Verge: Google announces Gemini Intelligence, bundling existing and new Gemini features, including task automation across apps and vibe-coding own Android widgets — We're one ste

model-releasestechmeme

12 May 2026

Google debuts Gemini Intelligence automation features, Googlebook laptop series

model-releasessiliconangle

Google LLC is upgrading its consumer device portfolio with a set of Android features called Gemini Intelligence and a new laptop series. The company debuted the products today during a virtual event c

Google DeepMind details a Gemini-powered mouse pointer that understands what it is pointing at, allowing users to perform tasks without using text-heavy prompts (Google DeepMind)

Google DeepMind: Google DeepMind details a Gemini-powered mouse pointer that understands what it is pointing at, allowing users to perform tasks without using text-heavy prompts — We are developing mo

model-releasestechmeme

Google launches Intrusion Logging, an Android feature developed in partnership with Amnesty International and others, on Android 16 Pixel devices for now (Tim Starks/CyberScoop)

Tim Starks / CyberScoop: Google launches Intrusion Logging, an Android feature developed in partnership with Amnesty International and others, on Android 16 Pixel devices for now — Intrusion Logging m

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GraphBench: Next-generation graph learning benchmarking

arXiv:2512.04475v5 Announce Type: replace-cross Abstract: Machine learning on graphs has made substantial progress across domains such as molecular property prediction and chip design. Yet benchmarkin

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs

arXiv:2605.09408v1 Announce Type: new Abstract: Link prediction (inferring missing or future connections between nodes in a graph) is a fundamental problem in network science with widespread applicati

Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking

arXiv:2605.10893v1 Announce Type: new Abstract: Large vision-language models suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by langu

Grounding the Score: Explicit Visual Premise Verification for Reliable Vision-Language Process Reward Models

arXiv:2603.16253v2 Announce Type: replace-cross Abstract: Vision-language process reward models (VL-PRMs) are increasingly used to score intermediate reasoning steps and rerank candidates under test-t

GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs

arXiv:2508.20325v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) become increasingly integral to various domains, their potential to generate harmful responses has prompted si

H-POPE: Hierarchical Polling-based Probing Evaluation of Hallucinations in Large Vision-Language Models

arXiv:2411.04077v2 Announce Type: replace Abstract: By leveraging both texts and images, large vision language models (LVLMs) have shown significant progress in various multi-modal tasks. Nevertheless

Hidden Error Awareness in Chain-of-Thought Reasoning: The Signal Is Diagnostic, Not Causal

arXiv:2605.09502v1 Announce Type: cross Abstract: Chain-of-thought (CoT) prompting assumes that generated reasoning reflects a model's internal computation. We show this assumption is wrong in a speci

HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving

arXiv:2605.09972v1 Announce Type: cross Abstract: End-to-end autonomous driving has witnessed rapid progress, yet existing benchmarks are increasingly saturated, with state-of-the-art models achieving

Hierarchical Reinforced Trader (HRT): A Bi-Level Approach for Optimizing Stock Selection and Execution

arXiv:2410.14927v2 Announce Type: replace-cross Abstract: Automated equity trading requires converting noisy market and news signals into executable portfolio decisions under risk, turnover, and trans

High Precision Hydraulic Excavator Control for Heavy-Duty Grading

model-releasesarxiv-cs-ro

arXiv:2605.09465v1 Announce Type: new Abstract: High-precision heavy-duty grading is a common step in earthworks, traditionally carried out manually by skilled operators. Removing a significant amount

Higher-Order Equilibrium Tracking for EM-Compressible Online Estimation

arXiv:2605.08864v1 Announce Type: new Abstract: We study online estimation in latent-variable models by recasting the problem as tracking a moving empirical equilibrium. Standard online EM and stochas

Higher Resolution, Better Generalization: Unlocking Visual Scaling in Deep Reinforcement Learning

arXiv:2605.10546v1 Announce Type: new Abstract: Pixel-based deep reinforcement learning agents are typically trained on heavily downsampled visual observations, a convention inherited from early bench

Hint Tuning: Less Data Makes Better Reasoners

arXiv:2605.08665v1 Announce Type: new Abstract: Large reasoning models achieve high accuracy through extended chain-of-thought but generate 5--8 more tokens than necessary, applying verbose reasoning

Holmes: A Benchmark to Assess the Linguistic Competence of Language Models

arXiv:2404.18923v5 Announce Type: replace Abstract: We introduce Holmes, a new benchmark designed to assess language models (LMs) linguistic competence - their unconscious understanding of linguistic

HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities

arXiv:2605.09348v1 Announce Type: cross Abstract: Large Language Models (LLMs) provide flexible natural language processing capabilities, while knowledge graphs (KGs) offer explicit and structured kno

HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editing

arXiv:2605.08143v1 Announce Type: cross Abstract: Large language models encode vast factual knowledge that inevitably becomes outdated or incorrect after deployment, yet retraining is costly prohibiti

How NVIDIA engineers and researchers build with Codex

NVIDIA engineers and researchers utilize OpenAI's Codex, a large language model trained on code, to accelerate software development and improve productivity across their engineering workflows. The art

model-releasesopenai

HS-FNO: History-Space Fourier Neural Operator for Non-Markovian Partial Differential Equations

arXiv:2605.09523v1 Announce Type: new Abstract: Neural operators provide fast surrogate models for time-dependent partial differential equations, but their standard autoregressive use usually assumes

Human-Inspired Memory Architecture for LLM Agents

arXiv:2605.08538v1 Announce Type: new Abstract: Current LLM agents lack principled mechanisms for managing persistent memory across long interaction horizons. We present a biologically-grounded memory

Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care

arXiv:2605.08533v1 Announce Type: new Abstract: Clinical decision-making in emergency medicine demands rapid, accurate diagnoses under uncertainty. Despite benchmark progress, evidence for LLMs as int

Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

arXiv:2501.12202v4 Announce Type: replace Abstract: We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two fo

HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations

arXiv:2604.15113v2 Announce Type: replace Abstract: Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We int

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation

arXiv:2605.10009v1 Announce Type: new Abstract: Query-based image retrieval (QBIR) requires retrieving relevant images given diverse and often stylistically heterogeneous queries, such as sketches, ar

I love seeing a new eval with such low scores. When we announced GPT-5.5, almost every benchmark had a score above 50%. It's time to retire …

model-releasesgary-marcus--x

I love seeing a new eval with such low scores. When we announced GPT-5.5, almost every benchmark had a score above 50%. It's time to retire evals like GQPA and bring in a new set. The first ProgramBen

I needed to book flights for a bunch of upcoming travel. As always, I used Claude Cowork to do it. In the past, Cowork has been decent at bo…

model-releasesboris-cherny--x

I needed to book flights for a bunch of upcoming travel. As always, I used Claude Cowork to do it. In the past, Cowork has been decent at booking flights, but with Opus 4.7, for the first time ever, i

I put my flight preferences in my Cowork instructions, then let Opus get to work. It opened my browser, navigated a bunch of websites, and b…

model-releasesboris-cherny--x

I put my flight preferences in my Cowork instructions, then let Opus get to work. It opened my browser, navigated a bunch of websites, and booked everything for me. The result: Cowork booked 8 flights

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics

arXiv:2403.18136v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have gained popularity in numerous domains, yet they are vulnerable to backdoor attacks that can compromise their

Identifying Multi-Hit Cancer Drivers Without Massive Parallelization: A CP, MIP, and Column Generation Framework

arXiv:2602.22551v2 Announce Type: replace-cross Abstract: Cancer is often driven by specific combinations of an estimated two to nine gene mutations, known as multi-hit combinations. Identifying these

Idira launches as Palo Alto Networks extends CyberArk tech to machine and agentic identities

model-releasessiliconangle

Palo Alto Networks Inc. today launched Idira, a new identity security platform designed to manage human, machine and artificial intelligence agent identities across the enterprise under a single privi

Illusion-Aware Visual Preprocessing and Anti-Illusion Prompting for Classic Illusion Understanding in Vision-Language Models

arXiv:2605.08841v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit systematic bias toward visual illusions, recalling memorized facts rather than perceiving actual visual difference

Improving Generalization by Permutation Routing Across Model Copies

arXiv:2605.09256v1 Announce Type: cross Abstract: We introduce a use of the (M)-cover (or (M)-layer) transform for machine learning. The method replicates a model (M) times, but instead of coupling th

Improving TMS EEG Signal Quality for Closed-Loop Neuro Stimulation via Source-Domain Denoising

arXiv:2605.08184v1 Announce Type: cross Abstract: This research addresses a validated TMS EEG cleaning pipeline and a corresponding benchmark dataset. It evaluates two widely used artifact removal pip

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.…

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.' @jpineau1, Chief AI Officer at @Cohere at #WebSummitVancou

model-releasescohere--x

In-Context Fixation: When Demonstrated Labels Override Semantics in Few-Shot Classification

arXiv:2605.08295v1 Announce Type: cross Abstract: While random demonstration labels barely hurt in-context learning (Min et al., 2022), we show that homogeneous labels--even semantically valid ones--c

Incremental Multilingual Text2Cypher with Adapter Combination

arXiv:2601.16097v2 Announce Type: replace Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, whi

IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

arXiv:2605.10267v1 Announce Type: new Abstract: In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every par

Instruction Adherence in Coding Agent Configuration Files: A Factorial Study of Four File-Structure Variables

arXiv:2605.10039v1 Announce Type: cross Abstract: Frontier coding agents read configuration files (CLAUDE.md, AGENTS.md, Cursor Rules) at session start and are expected to follow the conventions insid

Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions

arXiv:2605.09870v1 Announce Type: cross Abstract: We propose SVAR-FM (Structural VAR with Flow Matching), a framework for time series causal discovery that treats a physics-based simulator as a mechan

Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning

arXiv:2605.08233v1 Announce Type: cross Abstract: Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to sin

IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts

arXiv:2605.08664v1 Announce Type: new Abstract: Current image quality assessment methods are heavily biased towards global distortions (e.g., noise, blur), neglecting local perceptual artifacts such a

Is Your Driving World Model an All-Around Player?

arXiv:2605.10858v1 Announce Type: new Abstract: Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic tex

'It is categorically not a victory for pure LLMs; it’s a victory for borrowing from classical AI and CS to move beyond pure LLMs.' ☝️ Co…

model-releasesgary-marcus--x

'It is categorically *not* a victory for pure LLMs; it’s a victory for borrowing from classical AI and CS to move *beyond* pure LLMs.' ☝️ Compound AI Systems alllll the way downnn 🤩🤯🤩 Claude Code (sti

ITLC at SemEval-2026 Task 11: Normalization and Deterministic Parsing for Formal Reasoning in LLMs

arXiv:2603.02676v2 Announce Type: replace-cross Abstract: Large language models suffer from content effects in reasoning tasks, particularly in multi-lingual contexts. We introduce a novel method that