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Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

arXiv:2509.15908v3 Announce Type: replace-cross Abstract: Nanoporous materials hold promise for diverse sustainable applications, yet their vast chemical space poses challenges for efficient design. M

local-aiarxiv-cs-ai

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Introducing AI Browser Games! Watch open & closed models build small browser games head to head. Open models like Kimi K2.7 were faster, che…

DGX agent

Introducing AI Browser Games! Watch open & closed models build small browser games head to head. Open models like Kimi K2.7 were faster, cheaper, & produced games similar to Opus 4.8. In some cases, o

toolstogether-ai--x

7 Jul 2026

Introducing Flint Ads Agent: we optimize your Google Ads spend for you. Our agent figures out what’s costing you conversions, using our comp…

Introducing Flint Ads Agent: we optimize your Google Ads spend for you. Our agent figures out what’s costing you conversions, using our comprehensive data and optimization engine. Then, it executes th

agentsharrison-chase--x

Inverse Design of Metainterfaces for Static Friction Control: Beyond the Hertzian Limit

arXiv:2605.11012v2 Announce Type: cross Abstract: Programming the static friction of mechanical interfaces is critical for soft robotics, haptics, and precision gripping. Static friction is governed b

InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem

arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina

researcharxiv-cs-ai

InverseScope: Scalable Activation Inversion for Interpreting Large Language Models

arXiv:2506.07406v3 Announce Type: replace-cross Abstract: Understanding the internal representations of large language models (LLMs) is a central challenge in interpretability research. Existing featu

researcharxiv-cs-ai

Invisible Strings: Deriving Puppetry Principles and their Hidden Connections to Robot Behavior Design

arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these

applicationsarxiv-cs-ro

IPDiff: Diffusion-driven ORSI Salient Object Detection with Information Reconstruction and Multi-Prior Guidance

arXiv:2607.03696v1 Announce Type: new Abstract: Existing Salient Object Detection in Optical Remote Sensing Image (ORSI-SOD) methods mainly adopt the static inference strategy, which uses fixed traine

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

arXiv:2605.06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than expl

IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation

arXiv:2512.10730v2 Announce Type: replace Abstract: Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowled

IRIS: An Intelligent Vision-Language System for Ocular Surface Diseases via Topic Tree and Scene-Driven VQA Generation

arXiv:2607.04344v1 Announce Type: cross Abstract: While Large Vision-Language Models (VLMs) demonstrate remarkable generic capabilities, their clinical reasoning in specialized domains like ocular sur

Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild

arXiv:2607.03316v1 Announce Type: cross Abstract: Agentic code review, where autonomous agents provide code review comments on pull requests, is increasingly integrated into development workflows, yet

agentsarxiv-cs-ai

is anyone standardizing on ATIF as a format for agent traces? or a different format? or is it still wild wild west, roll your own

This post discusses the current state of standardization for agent execution trace formats, questioning whether ATIF (Agent Trace Interchange Format) or alternative formats have achieved adoption, or

agentsharrison-chase--x

Is Generation Required for Data-Efficient Perception?

arXiv:2512.08854v3 Announce Type: replace Abstract: It has been hypothesized that achieving the data efficiency of human visual perception requires a generative approach in which internal representati

researcharxiv-cs-cv

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models

arXiv:2607.05268v1 Announce Type: new Abstract: Whether a hyperbolic representation model uses its geometry cannot be read off its curvature parameter: what matters is the dimensionless operating poin

Is Your Benchmark Still Useful? Dynamic Benchmarking for Code Language Models

model-releasesarxiv-cs-cl

arXiv:2503.06643v2 Announce Type: replace-cross Abstract: In this paper, we tackle a critical challenge in model evaluation: how to keep code benchmarks useful when models might have already seen them

Iterative Visual Thinking and the Self-Correction Mirage in VLM Grounding

arXiv:2606.13156v2 Announce Type: replace-cross Abstract: Letting a vision-language model (VLM) think longer at test time has driven much recent progress. A natural way to bring this to spatial ground

safetyarxiv-cs-ai

It's all In the (Exponential) Family: An Equivalence between Maximum Likelihood Estimation and Control Variates for Sketching Algorithms

arXiv:2601.22378v3 Announce Type: replace-cross Abstract: Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching

Industry

It's time to get out of stealth 👋 Today, we are launching @monogram_ai and announcing our $40m seed round led by DST and Lux Capital. Monog…

It's time to get out of stealth 👋 Today, we are launching @monogram_ai and announcing our $40m seed round led by DST and Lux Capital. Monogram is the first AI app that was built around a visual interf

industryarthur-mensch--x

iVISION-2DCD: A Long-Term Change Detection Dataset for Large-Scale Outdoor Construction Monitoring

arXiv:2607.03553v1 Announce Type: new Abstract: Automation in construction is essential for reducing costs and human errors in large-scale projects. We approach the construction progress monitoring fr

JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference

arXiv:2512.22999v2 Announce Type: replace-cross Abstract: We consider problems of parameter estimation where design variables can be actively optimized to maximize information gain. To this end, we in

JavaVulBench: A Java Vulnerability Benchmark with Realistic Splits, a Unified Multi-Backend Harness, and a Leakage-Aware Evaluation Mode

arXiv:2607.02825v1 Announce Type: cross Abstract: We release extsc{JavaVulBench}, a benchmark dataset and evaluation harness for Java vulnerability detection. The dataset contains sim30{,}600 Java met

@JohnNguyen and I are presenting the Beyond Language Modeling paper as an ICML spotlight in 30 minutes at the 10:30 AM poster session! I…

@__JohnNguyen__ and I are presenting the Beyond Language Modeling paper as an ICML spotlight in 30 minutes at the 10:30 AM poster session! I’ll also be at the AMI Mixer on Thursday and hanging around

researchyann-lecun--x

Joint distribution of upstream runoff governs downstream river-discharge prediction uncertainty in distributed ML models

arXiv:2607.03217v1 Announce Type: new Abstract: Uncertainty quantification of hydrological predictions is necessary to inform operational decisions. Recent generative machine-learning methods have adv

applicationsarxiv-cs-lg

Joint Velocity Slope Diffusion Prior for Structurally Constrained Velocity Model Building

arXiv:2607.04982v1 Announce Type: cross Abstract: High-resolution velocity models are crucial for reservoir characterization and subsurface delineation. However, the band limited nature of our surface

local-aiarxiv-cs-ai

Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion

arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi

researcharxiv-cs-cl

K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos

arXiv:2607.02680v1 Announce Type: cross Abstract: MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text. A crucial, yet underexplored, appl

kAgent: An execution-guided crash resolution agent for the Linux kernel

arXiv:2504.20412v3 Announce Type: replace-cross Abstract: Fuzzing frameworks like syzkaller have uncovered thousands of Linux kernel crashes, many of which are critical and security-sensitive. However

agentsarxiv-cs-ai

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo

local-aiarxiv-cs-ai

KAM-WM: Kinematic Affordance Maps from Latent World Models for Robot Manipulation

arXiv:2607.04652v1 Announce Type: new Abstract: Learning manipulation from few demonstrations requires visual priors that capture not only where to interact, but also how the interaction should begin;

local-aiarxiv-cs-ro

KAN vs LSTM Performance in Time Series Forecasting

arXiv:2511.18613v2 Announce Type: replace-cross Abstract: This study presents a controlled comparison of baseline Kolmogorov-Arnold Networks (KAN), implemented via PyKAN, and Long Short-Term Memory (L

researcharxiv-cs-ai

karl. -- A Research Vehicle for Automated and Connected Driving

arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel

applicationsarxiv-cs-ro

KARMA: Knowledge graph-based Automated Reasoning Materialization and Alignment

arXiv:2607.03166v1 Announce Type: cross Abstract: Template-based contrastive synthesis is scalable, but its candidates often differ only in a few entity-slots while sequence-level optimization spreads

safetyarxiv-cs-ai

Industry

Keyfactor, which manages billions of machine identities for more than 2,500 client organizations, raised $1B+ led by Summit Partners (Mike Lennon/SecurityWeek)

Mike Lennon / SecurityWeek: Keyfactor, which manages billions of machine identities for more than 2,500 client organizations, raised $1B+ led by Summit Partners — The investment will accelerate Keyfac

industrytechmeme

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic

Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG

arXiv:2508.02296v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are increasingly deployed in high-stakes domains, where safety depends not only on how a system answers

safetyarxiv-cs-cl

Knowing When to Stop: Predicting Execution-Consistency Convergence in Text-to-SQL

model-releasesarxiv-cs-cl

arXiv:2607.03991v1 Announce Type: cross Abstract: Repeated LLM calls are the standard way to estimate how trustworthy a Text-to-SQL result is: run the pipeline multiple times, judge each SQL execution

Knowledge-Centric Information Systems

arXiv:2607.02609v1 Announce Type: cross Abstract: For decades, data engineering has developed mature architectural principles for integrating, governing, validating, cataloging, and serving organizati

applicationsarxiv-cs-ai

Knowledge-Informed Local Causal Discovery of Optimal Adjustment Sets

arXiv:2607.04447v1 Announce Type: new Abstract: Local causal discovery is a scalable alternative to global structure learning. However, it can struggle to identify valid adjustment sets in data-scarce

applicationsarxiv-cs-lg

Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMs

arXiv:2607.05013v1 Announce Type: new Abstract: Although LLMs have made significant progress in mathematical reasoning, determining whether a mathematical problem is solvable remains a fundamental yet

researcharxiv-cs-cl

KVpop -- Key-Value Cache Compression with Predictive Online Pruning

arXiv:2607.05061v1 Announce Type: new Abstract: Key-value (KV) cache growth is a major bottleneck in autoregressive decoding, as memory and bandwidth scale linearly with context length. Existing KV ev

safetyarxiv-cs-lg

Labeled-Data-Free Meta-Learning: Efficient Task Generation Using Pre-trained Models and Unlabeled Data

arXiv:2607.02850v1 Announce Type: new Abstract: Meta-learning without labeled data is crucial for real-world applications, where obtaining labeled datasets can be expensive or restricted due to privac

applicationsarxiv-cs-lg

LACE-SVD: Loss-Aware SVD with Cumulative Error Correction for LLM Compression

arXiv:2607.03057v1 Announce Type: cross Abstract: The rapid growth in the parameter scale of large language models (LLMs) has created a strong demand for efficient compression techniques. As a hardwar

Lacuna Inc. at SemEval-2026 Task 4: Structurally Gated State-Space Models for Disentangling Narrative Similarity

arXiv:2607.03482v1 Announce Type: new Abstract: In this paper, we present the Invariant-Variant Disentangled State-Space Model (IVD-SSM), our submission to SemEval-2026 Task 4 on Narrative Story Simil

safetyarxiv-cs-cl

LangLoc: 'Tell Me What You See'

arXiv:2607.05077v1 Announce Type: new Abstract: We tackle fine-grained indoor localization from natural language: given a free-form description of one's surroundings, estimate the observer's 2D positi

Language Generation with Replay: A Learning-Theoretic View of Model Collapse

arXiv:2603.11784v2 Announce Type: replace Abstract: As scaling laws push the training of frontier large language models (LLMs) toward ever-growing data requirements, training pipelines are approaching

Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments

arXiv:2412.13533v4 Announce Type: replace Abstract: Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown prom

Language Models as Higher-Order Planning Formalizers

arXiv:2603.23844v2 Announce Type: replace Abstract: Recent work provides overwhelming evidence that LLMs, even those trained to scale their reasoning trace, quickly deteriorate at planning as problems

researcharxiv-cs-cl