Search: “reasoning”

SEAL: Can Saturated Benchmarks Be Revived by LLM-as-a-Meta-Judge?

arXiv:2605.30104v1 Announce Type: new Abstract: Widely used language-model benchmarks are increasingly saturated, with frontier systems often receiving near-tied scores that standard metrics cannot re

agentsarxiv-cs-cl

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SwInception -- Local Attention Meets Convolutions

DGX agent

arXiv:2605.29954v1 Announce Type: new Abstract: Sparse vision transformers have gained popularity as efficient encoders for medical volumetric segmentation, with Swin emerging as a prominent choice. S

model-releasesarxiv-cs-cv

29 May 2026

The Complexity of Verifying Feedforward Neural Networks in Quantised Settings

arXiv:2605.29537v1 Announce Type: cross Abstract: We investigate the computational complexity of neural network verification in quantised settings. We distinguish three classes of Feedforward Neural N

researcharxiv-cs-lg

Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback

arXiv:2605.29141v1 Announce Type: cross Abstract: Traditional recommender systems (RecSys) primarily infer user preferences from implicit signals (such as clicks, watches, and purchases), often neglec

safetyarxiv-cs-ai

Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation

arXiv:2605.29430v1 Announce Type: new Abstract: Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly important front-end for LLM-based assistants a

safetyarxiv-cs-ai

Training Deliberative Monitors for Black-Box Scheming Detection

arXiv:2605.29601v1 Announce Type: cross Abstract: As autonomous agents become more capable of performing real-world tasks, distinguishing scheming behavior from benign task pursuit may become a centra

Unveiling the Visual Counting Bottleneck in Vision-Language Models

arXiv:2605.30170v1 Announce Type: cross Abstract: While Large Vision-Language Models (VLMs) excel at interpolation, they suffer catastrophic failures in systematic generalization, most notably in visu

researcharxiv-cs-cv

User-Aware Active Knowledge Acquisition for Emotional Support Dialogue

arXiv:2605.29715v1 Announce Type: new Abstract: Emotional support plays an important role in dialogue systems, and its success depends on adapting to a user's evolving and implicit needs across multi-

safetyarxiv-cs-cl

Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering

arXiv:2605.29648v1 Announce Type: new Abstract: Applying reinforcement learning to improve factual accuracy in knowledge-intensive question answering faces a reward design dilemma. Response-level rewa

VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis

arXiv:2605.28978v1 Announce Type: new Abstract: Finite Element Analysis (FEA) serves as the cornerstone of modern engineering design. However, its workflow is inherently complex and relies heavily on

agentsarxiv-cs-ai

Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence

arXiv:2605.29744v1 Announce Type: new Abstract: The impressive performance of generalist large language models (LLMs) such as GPT and Claude in healthcare raises a critical question: will domain-speci

.@ylecun’s definition of what is a world model.

Yann LeCun, a pioneering AI researcher, provides his definition of what constitutes a world model in this X post. A world model is an AI system's internal representation of how the physical world work

researchyann-lecun--x

YoCausal: How Far is Video Generation from World Model? A Causality Perspective

model-releasesarxiv-cs-cv

arXiv:2605.30346v1 Announce Type: new Abstract: As video diffusion models (VDMs) advance toward world models, a key question arises: do they truly understand causality, or merely overfit to statistica

Adaptive Cost-Efficient Evaluation for Reliable Patent Claim Generation

arXiv:2604.04295v3 Announce Type: replace Abstract: Automated patent claim validation demands low error tolerance. However, existing approaches face a rigidity-resource dilemma: lightweight encoders c

AI in SRE: Where and how Google is deploying agentic AI to improve operations

model-releasesgoogle-cloud-ai

Since its inception over 20 years ago, Google has used Site Reliability Engineering (SRE) to keep services like Search, Gmail, Maps, YouTube and Google Cloud reliable and highly available, adhering to

AndroidDaily: A Verifiable Benchmark for Mobile GUI Agents on Real-World Closed-Source Applications

model-releasesarxiv-cs-cv

arXiv:2605.27761v1 Announce Type: new Abstract: The rapid development of GUI foundation models and mobile GUI agents has spurred numerous evaluation benchmarks, yet most rely on simulated environments

Apple working to cram massive Gemini model into iPhone to power new Siri

model-releasesars-technica

Apple is reportedly working to distill knowledge and skills from Google's larger Gemini model into a smaller version that could run on iPhones. The new Siri will use a tiered system where simple tasks

AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios

arXiv:2605.27995v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations oft

Tutorials

Automatic Pruning Discovery for Large Language Models

arXiv:2511.15390v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on a wide range of tasks, hindering real-world deployment due to their massive siz

tutorialsarxiv-cs-cv

Automating Formal Verification with Agent-Guided Tree Search

model-releasesarxiv-cs-lg

arXiv:2605.27485v1 Announce Type: cross Abstract: Formal verification offers a path to provably correct software, but writing verified code remains expensive enough that the technique is rarely used i

Benchmarking and Mechanistic Analysis of Vision-Language Models for Cross-Depiction Assembly Instruction Alignment

arXiv:2604.00913v2 Announce Type: replace-cross Abstract: 2D assembly diagrams are often abstract and hard to follow, creating a need for intelligent assistants that can monitor progress, detect error

Category-Level 3D Correspondence in Camera Space via Morphable Object Priors

model-releasesarxiv-cs-cv

arXiv:2605.28257v1 Announce Type: new Abstract: Understanding 3D objects from images is fundamental to robotics and AR/VR applications. While recent work has made progress in category-level pose estim

Causal Machine Learning: A Survey and Open Problems

arXiv:2206.15475v3 Announce Type: replace Abstract: Causal Machine Learning (CausalML) is an umbrella term for machine learning methods that formalize the data-generation process as a structural causa

safetyarxiv-cs-lg

Chain-based Adaptive Reconfiguration Over Lattices for Hallucination Reduction

arXiv:2605.27706v1 Announce Type: new Abstract: We introduce CAROL (Chain-based Adaptive Reconfiguration Over Lattices), a probabilistic framework for test-time hallucination reduction in large langua

agentsarxiv-cs-cl

CircuitLM: A Multi-Agent LLM-Aided Design Framework for Generating Circuit Schematics from Natural Language Prompts

arXiv:2601.04505v3 Announce Type: replace Abstract: Generating accurate circuit schematics from high-level natural language descriptions remains a persistent challenge in electronic design automation

agentsarxiv-cs-ai

Local Ai

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models

arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods the

local-aiarxiv-cs-ai

ClinConsensus: A Physician-Calibrated Benchmark for Evaluating Clinical Rubric Coverage in Chinese Medical LLMs

arXiv:2603.02097v5 Announce Type: replace Abstract: Open-ended medical LLM evaluation remains weakly grounded in physician-calibrated coverage of clinically relevant response criteria, especially in l

Con-DSO: Learning Short-Horizon Consistency Priors for RGB-D Direct Sparse Odometry

arXiv:2605.27952v1 Announce Type: new Abstract: Visual odometry (VO) is a fundamental component in robotics and augmented reality. RGB-D direct VO benefits from metric depth measurements, but it can d

safetyarxiv-cs-cv

ConRAG: Consensus-Driven Multi-View Retrieval for Multi-Hop Question Answering

arXiv:2605.28093v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) has emerged as a promising paradigm for enhancing large language models (LLMs) on multi-hop question answering (QA)

Cultural Binding Heads in Language Models

arXiv:2605.28543v1 Announce Type: new Abstract: LLMs often default to equal treatment across cultural groups, even though context warrants differentiation: this is a lack of difference awareness. Usin

CyberJurors: A Multi-Agent Simulation Task for E-Commerce Disputes Verdict

arXiv:2605.28369v1 Announce Type: new Abstract: E-commerce platforms have begun recruiting crowdsourced jurors to adjudicate massive volumes of transaction disputes. Unlike formal legal judgment, E-co

DeepSciVerify: Verifying Scientific Claim--Citation Alignment via LLM-Driven Evidence Escalation

arXiv:2605.27710v1 Announce Type: new Abstract: Misalignment between claims and their cited evidence is a common failure mode in reports generated by large language models, limiting their reliability

Applications

EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction

arXiv:2605.28101v1 Announce Type: cross Abstract: Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive s

applicationsarxiv-cs-ai

Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data

model-releasesarxiv-cs-lg

arXiv:2605.27618v1 Announce Type: new Abstract: Despite the wide use of explainability techniques to attempt to understand the behavior of Artificial Intelligence (AI), the generated explanations may

Evolving Dataflow to process massive datasets for machine learning

model-releasesgoogle-cloud-ai

Google created MapReduce more than 20 years ago to solve the scaling problems in data processing that the then young company was running into. The AI era that we are in now demands efficient, large-sc

Explaining is Harder Than Predicting Alone: Evaluating Concept-based Explanations of MLLMs as ICL Visual Classifiers

arXiv:2605.28215v1 Announce Type: new Abstract: In-context learning (ICL) enables multimodal large language models (MLLMs) to classify images from a few labelled examples. Yet, how these models use th

researcharxiv-cs-ai

Extracting Small Translation Specialists from LLMs by Aggressively Pruning Experts

arXiv:2605.28042v1 Announce Type: cross Abstract: Modern large language models (LLMs) achieve state-of-the-art machine translation performance, but they do so as broad generalists largely trained for

researcharxiv-cs-ai

Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL

arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w

agentsarxiv-cs-ai

FPMoE: A Sparse Mixture-of-Experts Approach to Functional Code Generation

arXiv:2605.27849v1 Announce Type: cross Abstract: Despite rapid progress in LLM-based code generation, existing models are predominantly trained on imperative languages, leaving functional programming

Applications

From Causal Discovery to Dynamic Causal Inference in Neural Time Series

arXiv:2603.20980v2 Announce Type: replace-cross Abstract: Time-varying causal models provide a powerful framework for studying dynamic scientific systems, yet most existing approaches assume that the

applicationsarxiv-cs-ai

Applications

GEM: Generative Supervision Helps Embodied Intelligence

arXiv:2605.28548v1 Announce Type: new Abstract: Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Acti

applicationsarxiv-cs-cv

Gradient Transformer: Learning to Generate Updates for LLMs

model-releasesarxiv-cs-lg

arXiv:2605.27591v1 Announce Type: new Abstract: Many organizations lack computational resources to fine-tune large language models (LLMs) on private (unshareable) data for better utility, while fine-t

Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks

arXiv:2605.27595v1 Announce Type: cross Abstract: Large Language Models (LLMs) are being rapidly adopted in agricultural imaging applications, ranging from crop interpretation to synthetic field image

Harness-Bench: Measuring Harness Effects across Models in Realistic Agent Workflows

arXiv:2605.27922v1 Announce Type: new Abstract: LLM agents are increasingly deployed as executable systems that use tools, modify workspaces, and produce concrete artifacts. In such workflows, perform

Hermes Agent v0.15.0 - “The Velocity Release” Changelog below

Hermes Agent v0.15.0, released by Nous Research as 'The Velocity Release,' represents an update to their Hermes Agent framework that likely focuses on performance improvements and speed optimizations.

agentsnous-research--x

Interpretability-Guided Layer Selection over Subspace Projection: SAEs as Stethoscopes, Not Scalpels, for Raw Task Vector Model Editing

arXiv:2605.28649v1 Announce Type: cross Abstract: LLMs increasingly require surgical model editing to enhance domain-specific capabilities without incurring the computational cost or catastrophic forg

IPO-Mine: A Toolkit and Dataset for Section-Structured Analysis of Long, Multimodal IPO Documents

arXiv:2605.28714v1 Announce Type: cross Abstract: An Initial Public Offering (IPO) filing is a document released when a private firm goes public, allowing individual (retail) investors to purchase its

Knowing When to Ask: Segment-Level Credit Assignment for LLM Tool Use

arXiv:2605.27788v1 Announce Type: cross Abstract: Humans know when to reach for help e.g. 347 imes 28 warrants a calculator while 2+2 does not. Language models do not. Prompt-based approaches can inst

agentsarxiv-cs-cl