Search: “reasoning”

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity

arXiv:2607.00248v1 Announce Type: new Abstract: We present Seed2.0, a model series that takes a meaningful step toward solving complex, real-world tasks. Our approach begins with identifying users' ge

applicationsarxiv-cs-ai

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Shapley in Context: Explaining Financial Language with Domain Expertise

DGX agent

arXiv:2607.00856v1 Announce Type: cross Abstract: In recent years, large language models have achieved remarkable success and have seen growing adoption in financial applications. At the same time, ex

applicationsarxiv-cs-lg

2 Jul 2026

SlowBA: An efficiency backdoor attack towards VLM-based GUI agents

arXiv:2603.08316v3 Announce Type: replace-cross Abstract: Modern vision-language-model (VLM) based graphical user interface (GUI) agents are expected not only to execute actions accurately but also to

agentsarxiv-cs-cl

Structured 4D Latent Predictive Model for Robot Planning

arXiv:2607.01166v1 Announce Type: cross Abstract: Video predictive models are emerging as a powerful paradigm in robotics, offering a promising path toward task generalization, long-horizon planning,

applicationsarxiv-cs-cv

SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests

arXiv:2607.00990v1 Announce Type: cross Abstract: Large language model (LLM)-based software engineering agents are increasingly developed to resolve software issues by generating patches from issue re

The Narrative Strategy of Sam Altman on CNBC today… Some notes from discussing this ‘we will give America 5% of OpenAI’ idea… 1 - Strategica…

The Narrative Strategy of Sam Altman on CNBC today… Some notes from discussing this ‘we will give America 5% of OpenAI’ idea… 1 - Strategically it makes sense for OpenAI to Invite This Matrix-multipli

researchyann-lecun--x

Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics

model-releasesarxiv-cs-lg

arXiv:2607.00969v1 Announce Type: cross Abstract: Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approach

Understanding Large Language Models

arXiv:2607.01006v1 Announce Type: new Abstract: Large Language Models (LLMs) represent one of the most significant advances in AI and natural language processing in recent years. Still, many pressing

researcharxiv-cs-cl

UniDrive-WM: Unified Understanding, Planning and Generation World Model for Autonomous Driving

arXiv:2601.04453v4 Announce Type: replace Abstract: World models have become central to autonomous driving, where accurate scene understanding and future prediction are crucial for safe control. Recen

When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets

arXiv:2512.04988v2 Announce Type: replace-cross Abstract: Emerging agentic marketplaces provide the economic infrastructure for matching and coordinating the large amounts of AI agents used in agentic

ZO-Act: Efficient Zeroth-Order Fine-Tuning via One-Shot Activation-Informed Low-Rank Subspaces

model-releasesarxiv-cs-lg

arXiv:2607.01125v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization enables fine-tuning large language models when backpropagation is unavailable or memory-prohibitive, but existing methods

Adaptive Cluster-First Route-Second Decomposition for Industrial-Scale Vehicle Routing

arXiv:2606.31820v1 Announce Type: new Abstract: Large-scale capacitated vehicle routing problems (CVRPs) are commonly addressed using cluster-first route-second (CFRS) approaches that split a routing

Agentic retrieval is changing the way retrieval-augmented applications are built, especially in domains like legal and fintech, where agents…

model-releasesllamaindex--x

Agentic retrieval is changing the way retrieval-augmented applications are built, especially in domains like legal and fintech, where agents need to autonomously navigate large, evolving knowledge bas

AlloyDB AI Functions - now with revolutionary performance boosts and cost savings

model-releasesgoogle-cloud-ai

AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% ac

ALM2Vec: Learning Audio Embeddings for Universal Audio Retrieval with Large Audio-Language Models

arXiv:2606.30682v1 Announce Type: cross Abstract: Recent advances in language--audio retrieval have been largely driven by contrastive dual-encoder architectures that align audio and text in a shared

An Agentic AI Framework to Accelerate Scientific Discovery in Plant Phenotyping

arXiv:2606.31831v1 Announce Type: new Abstract: High-throughput plant phenotyping now generates image derived datasets far faster than scientists can analyze them. At Oak Ridge National Laboratory's A

ARC-AGI-3 is built different, it has dumbfounded almost all regular attempts so far because it's so much harder than anything that came befo…

model-releasesfrancois-chollet--x

ARC-AGI-3 is built different, it has dumbfounded almost all regular attempts so far because it's so much harder than anything that came before. It has no rules, it's agentic and has no explicit goals,

BayesBench: Evaluating LLM Belief Trajectories Under Multi-Turn Evidence Accumulation

arXiv:2606.30850v1 Announce Type: new Abstract: Large language models (LLMs) are typically deployed in multi-turn conversations, where each turn provides new evidence that should reduce epistemic unce

Benchmarking Large Language Models on Floating-Point Error Classification

arXiv:2606.31308v1 Announce Type: new Abstract: This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code. We intr

Beyond But-for Test: Counterfactual Explanation in Abstract Argumentation via Actual Causality (Extended Version)

arXiv:2606.31080v1 Announce Type: cross Abstract: Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the statu

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning

arXiv:2502.00684v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has successfully addressed many complex control problems. However, the neural networks representing policies

Contrastive Reflection for Iterative Prompt Optimization

arXiv:2606.30840v1 Announce Type: new Abstract: LLM agents are becoming central to information retrieval: they issue retrieval queries, synthesize answers, and increasingly serve as judges for IR eval

Safety

DISCOVER: A Solver for Distributional Counterfactual Explanations

arXiv:2603.16436v2 Announce Type: replace Abstract: Counterfactual explanations (CE) explain model decisions by identifying input modifications that lead to different predictions. Most existing method

safetyarxiv-cs-lg

DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation

arXiv:2606.32028v1 Announce Type: new Abstract: Video-based embodied world models provide an appealing substrate for robotic manipulation by predicting future states, yet current approaches remain lim

applicationsarxiv-cs-ro

Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors

model-releasesarxiv-cs-cl

arXiv:2606.31845v1 Announce Type: new Abstract: A transformer's feed-forward (FFN) sublayer materializes the distinctions attention gathers, yet gives no account of what it computes. In a parameter-ne

Fable is very good, and having it taken away after getting early access delayed a few things I was working on and made me defer others until…

applicationsethan-mollick--x

Fable is very good, and having it taken away after getting early access delayed a few things I was working on and made me defer others until it returned But in my early access I also tripped the secur

Safety

From Failure to Alignment: A Requirements Engineering Framework for Machine Learning Systems

arXiv:2606.31589v1 Announce Type: cross Abstract: Organisations designing, developing, and deploying machine learning systems (MLS) need to be able to check that these systems are trustworthy, and com

safetyarxiv-cs-lg

From Search to Synthesis: Training LLMs as Zero-Shot Workflow Generators

arXiv:2606.30704v1 Announce Type: cross Abstract: Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed fo

Generative Skill Composition for LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.32025v1 Announce Type: new Abstract: Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for perfor

Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR

arXiv:2606.31813v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) and its variants enable parameter-efficient fine-tuning of large language models under the supervised fine-tuning (SFT) par

Local Ai

Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization

arXiv:2606.30813v1 Announce Type: cross Abstract: Deep neural networks with repeated architectural blocks, such as transformers, often exhibit structured relationships across layers that emerge during

local-aiarxiv-cs-ai

Improved Upper Bounds for Slicing the Hypercube

arXiv:2602.16807v2 Announce Type: replace Abstract: A collection of hyperplanes H slices all edges of the n-dimensional hypercube Q_n with vertex set {-1,1}^n if, for every edge e in the hypercube, th

Investigating Multi-Agent Deliberation in Law

arXiv:2606.30906v1 Announce Type: new Abstract: Artificial Intelligence is increasingly applied to the field of law, and has the potential to increase access to justice. One particular movement that i

Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

arXiv:2606.30987v1 Announce Type: new Abstract: Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Foreca

researcharxiv-cs-cl

MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs

arXiv:2606.31383v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) typically employ resampling-based projectors to transform dense visual features into a compact token sequence f

Multimodal Benchmark for Safety Assessment in Industrial Inspection Scenarios

arXiv:2601.21173v2 Announce Type: replace-cross Abstract: With the rapid development of industrial intelligence and unmanned inspection, reliable perception and safety assessment for AI systems in com

MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes

arXiv:2606.31533v1 Announce Type: new Abstract: Identifying and grounding precise geometric entities, such as edges, planar regions, and curved surfaces within 3D objects, is foundational to computer-

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs

arXiv:2606.31933v1 Announce Type: new Abstract: We introduce VidPair-Halluc, a new benchmark for evaluating video hallucination in large video models (LVMs) under rigorous and controlled conditions. U

Safety

Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments: Evidence from a Job Marketplace

arXiv:2606.30932v1 Announce Type: new Abstract: Two-sided marketplaces connect distinct user groups whose interests often conflict -- improving outcomes on one side could degrade the other side's expe

safetyarxiv-cs-lg

{Phi}eat: Physically Grounded Material Feature Representation

arXiv:2511.11270v2 Announce Type: replace Abstract: While foundation models have emerged as general-purpose visual backbones, their representations are primarily optimized for semantics and lack expli

Ponder This Challenge - July 2026 - Return of the Superheroes

IBM's July 2026 Ponder This Challenge likely presents a mathematical or logic puzzle with a superhero theme, continuing IBM Research's monthly series of recreational problem-solving challenges. The pu

researchibm-research

Random Reshuffling Dominates Stochastic Gradient Descent

arXiv:2606.32005v1 Announce Type: cross Abstract: Stochastic Gradient Descent (extsf{SGD}) is one of the most classical optimization algorithms with favorable theoretical guarantees, yet the practical

researcharxiv-cs-lg

Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

arXiv:2606.31616v1 Announce Type: new Abstract: Medical Artificial Intelligence (AI) is widely expected to transform clinical practice, yet the decision-making processes of many Machine Learning (ML)

SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

SOCRadar powers rapid threat detection with AlloyDB and Gemini Enterprise

model-releasesgoogle-cloud-ai

Editor’s note: SOCRadar is a leading cybersecurity company that provides threat intelligence to businesses worldwide. As the volume of cyber threats continued to grow, SOCRadar needed to modernize its

StemVLA:An Open-Source Vision-Language-Action Model with Future 3D Spatial Geometry Knowledge and 4D Historical Representation

arXiv:2602.23721v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising

Streaming Gaussian Encoding for 4D Panoptic Occupancy Tracking

arXiv:2606.30754v1 Announce Type: new Abstract: Camera-based 4D panoptic occupancy tracking (4D-POT) is a promising paradigm for holistic scene understanding from multi-view imagery, enabling joint re

T-QPM: Enabling Temporal Out-Of-Distribution Detection and Domain Generalization for Vision-Language Models in Open-World

arXiv:2603.18481v2 Announce Type: replace Abstract: Out-of-distribution (OOD) detection remains a critical challenge in open-world learning, where models must adapt to evolving data distributions. Whi