Search: “reasoning”

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling

arXiv:2606.28661v1 Announce Type: cross Abstract: People overthink; language models over-sample, and the extra effort can talk both into a worse answer. Reasoning systems answer a hard question by sam

30 Jun 2026

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Applications

COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives

DGX agent

arXiv:2606.28194v1 Announce Type: new Abstract: While interpretable models such as concept bottleneck models (CBMs) and program synthesis methods enable verification of model decisions, their evaluati

applicationsarxiv-cs-lg

29 Jun 2026

Democratic ICAI: Debating Our Way to Steering Principles from Preferences

arXiv:2606.28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criter

safetyarxiv-cs-lg

Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding

arXiv:2606.27596v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) exhibit sophisticated reasoning but remain susceptible to object hallucination. Deviating from the prevailing att

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs

model-releasesarxiv-cs-cl

arXiv:2606.27378v1 Announce Type: new Abstract: We introduce an axiomatic evaluation framework for latent thought representations in LLMs, comprising metrics that are independent of downstream benchma

Agents

GraphPilot: Grounded Scene Graph Conditioning for Language-Based Autonomous Driving

arXiv:2511.11266v4 Announce Type: replace Abstract: Vision-language models have recently emerged as promising planners for autonomous driving, where success hinges on topology-aware reasoning over spa

agentsarxiv-cs-cv

HiMu: Hierarchical Multimodal Frame Selection for Long Video Question Answering

arXiv:2603.18558v2 Announce Type: replace-cross Abstract: Long-form video question answering requires reasoning over extended temporal contexts, making frame selection a critical bottleneck for multi-

Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs

arXiv:2601.21233v2 Announce Type: replace Abstract: Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-d

safetyarxiv-cs-ai

Masked Language Flow Models

arXiv:2606.27617v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approxim

researcharxiv-cs-cl

Hardware

Nvidia CEO Jensen “@Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-t…

Nvidia CEO Jensen “@Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-to-end AI. Whether their AI did reasoning or not in somewhat

hardwareelon-musk--x

Ontology-Guided Evidence Path Inference for Multi-hop Knowledge Graph Question Answering

arXiv:2606.28076v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) aims to answer natural-language questions by reasoning over structured facts. Existing multi-hop KGQA methods

SidConArena: An Environment Evaluating Agents in Open-Ended,Positive-Sum Bargaining Game

arXiv:2606.27397v1 Announce Type: cross Abstract: Evaluating LLM agents requires dynamic environments that go beyond static reasoning and zero-sum games. Real-world economic interaction is often open-

Understanding How MLLMs Describe Artworks Using Token Activation Maps

arXiv:2606.27947v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When a

researcharxiv-cs-cv

When Search Agents Should Ask: DiscoBench for Clarification-Aware Deep Search

model-releasesarxiv-cs-cl

arXiv:2606.27669v1 Announce Type: new Abstract: Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval a

Did something happen to Opus 4.8 today? First time I've seen this happen (and I use it daily): it almost totally stopped thinking, even at h…

tutorialsjeremy-howard--x

Did something happen to Opus 4.8 today? First time I've seen this happen (and I use it daily): it almost totally stopped thinking, even at highest reasoning setting. And answered terribly. I repeated

28 Jun 2026

Applications

Every enterprise will have its own model-harness-sandbox-eval flywheel with token value per watt optimization. This is the future. Simple re…

applicationsclem-delangue--x

Every enterprise will have its own model-harness-sandbox-eval flywheel with token value per watt optimization. This is the future. Simple reason: tacit knowledge about the domain and customers and the

27 Jun 2026

If you use LLM-as-judge, this one is worth reading. (bookmark it) It's actually one of the most effective ways to use LLM-as-a-Judge for eva…

If you use LLM-as-judge, this one is worth reading. (bookmark it) It's actually one of the most effective ways to use LLM-as-a-Judge for evals. Holistic judge scores hide both their reasoning and thei

tutorialsdair-ai--x

27 Jun 2026

A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO

arXiv:2606.27188v1 Announce Type: new Abstract: We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacin

safetyarxiv-cs-ai

Accelerating Returns and the Qualitative Engine for Science

arXiv:2606.26359v1 Announce Type: new Abstract: Ray Kurzweil described a thesis of accelerating returns, which is the most influential narratives in discussions of technological progress. Its central

Beyond Logical Forms: LLM-Extracted Patterns for Fallacy Classification

arXiv:2606.26698v1 Announce Type: cross Abstract: In today's fast-paced information era, logical fallacies, defined as defective patterns of reasoning, inevitably contribute to the growth of informati

Applications

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs

arXiv:2606.26492v1 Announce Type: cross Abstract: Deep Learning (DL) programs can fail during training for many reasons, and diagnosing the cause is a costly and time-consuming maintenance task. Techn

applicationsarxiv-cs-ai

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models

arXiv:2606.26196v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have recently made remarkable progress in unifying vision-language understanding and reasoning, especially fo

@GaryMarcus, great interview and explanations of the challenges in AI. https://youtu.be/_pSivPlRx5o?is=dlFN6YBXsMA-tW4h

Gary Marcus discusses fundamental challenges and limitations in current AI systems during an interview, likely covering topics such as the gap between narrow and general intelligence, reasoning limita

safetygary-marcus--x

Industry

Good way to frame it. Also, if even one person had died, we would know who they were! Not one person has died from stopping waste & fraud at…

Good way to frame it. Also, if even one person had died, we would know who they were! Not one person has died from stopping waste & fraud at USAID! Obviously. One of the reasons that I don't accept th

industryelon-musk--x

Local Ai

Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models

arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod

local-aiarxiv-cs-ai

Applications

Many companies could build their own Workday or whatever, too, using open source alternatives. They don't do that for a wide variety of reas…

applicationsethan-mollick--x

Many companies could build their own Workday or whatever, too, using open source alternatives. They don't do that for a wide variety of reasons. Same dynamics apply in AI, only more so (upgrade cycles

Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models

arXiv:2602.01969v2 Announce Type: replace Abstract: Complex tables with multi-level headers, merged cells and heterogeneous layouts pose persistent challenges for LLMs in both understanding and reason

researcharxiv-cs-cl

Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models

arXiv:2606.27373v1 Announce Type: new Abstract: Recently, self-evolving large multimodal models (LMMs) have received attention for improving visual reasoning in a purely unsupervised setting. However,

safetyarxiv-cs-cv

Perception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection

arXiv:2606.26552v1 Announce Type: cross Abstract: The rapid advancement of generative models presents a significant challenge to existing deepfake detection methods, particularly given the widespread

PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editing

model-releasesarxiv-cs-cv

arXiv:2606.26551v1 Announce Type: new Abstract: While instruction-based image editing, enabled by multi-modal generative models, has advanced significantly, existing benchmarks lack a comprehensive ev

Qwen-Image-Agent: Bridging the Context Gap in Real-World Image Generation

model-releasesarxiv-cs-cv

arXiv:2606.26907v1 Announce Type: new Abstract: While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or d

Agents

SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills

arXiv:2606.26669v1 Announce Type: new Abstract: Agents often repeatedly solve similar task instances from scratch, leading to unnecessary reasoning cost and long execution traces. Prior work has explo

agentsarxiv-cs-ai

TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation

arXiv:2606.26874v1 Announce Type: new Abstract: Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLL

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference

arXiv:2606.27161v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved strong multimodal reasoning capabilities, but their efficiency is limited by the large number of

Visual-Language-Guided Task Planning for Horticultural Robots

model-releasesarxiv-cs-ro

arXiv:2601.11906v2 Announce Type: replace Abstract: Crop monitoring is essential for precision agriculture, but current systems lack high-level reasoning. We introduce a novel, modular framework that

Agents

AI SDK 7 is here. This release sets the foundation for agents and AI platforms in production: approvals, durability, telemetry, and more.

AI SDK 7 is here. This release sets the foundation for agents and AI platforms in production: approvals, durability, telemetry, and more. AI SDK 7 is now available. Introducing: reasoning control, age

agentsvercel--x

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation

arXiv:2606.25432v1 Announce Type: cross Abstract: Inference efficiency is typically pursued by shrinking the model: distillation, pruning, quantization, and sparse routing each lower per-token cost wh

researcharxiv-cs-cv

CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG

arXiv:2602.05143v2 Announce Type: replace Abstract: Retrieval augmented generation (RAG) has enhanced large language models by enabling access to external knowledge, with graph-based RAG emerging as a

Counterfeit Answers: Adversarial Forgery against OCR-Free Document Visual Question Answering

arXiv:2512.04554v2 Announce Type: replace Abstract: Document Visual Question Answering (DocVQA) enables end-to-end reasoning grounded on information present in a document input. While recent models ha

researcharxiv-cs-cv

Externalizing Research Synthesis and Validation in AI Scientists through a Research Harness

arXiv:2606.18874v2 Announce Type: replace Abstract: AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claim

How Complexity Contributes to Learning Opacity in Machine Learning

arXiv:2606.24953v1 Announce Type: new Abstract: Machine learning (ML) algorithms are known to be opaque. We do not know the reasons for their predictions. The learning process leading to the predictio

tutorialsarxiv-cs-lg

Measurable Majorities Are Not Finitely Axiomatizable

arXiv:2606.25954v1 Announce Type: cross Abstract: This theoretical note studies the finite axiomatizability of strict majority reasoning in finite social decision frames. Moss and Pedersen (2026) intr

Multi-Stream Temporal Fusion for Financial Fraud Detection

model-releasesarxiv-cs-lg

arXiv:2606.25007v1 Announce Type: new Abstract: Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams -- transactions, login sessions, risk signals

Or people could learn their lesson? Naah 🙈

Or people could learn their lesson? Naah 🙈 @GaryMarcus The reason he’s going down, is because the market can only handle one all encompassing scam at a time. So the AI scam will probably get a boost w

tutorialsgary-marcus--x

Position Spaces and Graphs

arXiv:2606.25719v1 Announce Type: new Abstract: In this paper, we introduce position graphs, a graph-based reasoning framework based on the formalization of position spaces. This framework utilizes tw

safetyarxiv-cs-ai

Small Initialization Matters for Large Language Models

arXiv:2606.17945v2 Announce Type: replace Abstract: Large language models provide a tractable system for asking how intelligence itself emerges, rather than only how LLMs can be engineered. Although p

SpeechEQ: Benchmarking Emotional Intelligence Quotient in Socially Aware Voice Conversational Models

model-releasesarxiv-cs-cl

arXiv:2606.25990v1 Announce Type: new Abstract: As multimodal conversational systems increasingly engage in spoken interaction, their ability to navigate paralinguistic social cues has become a critic

SSMNBench: Diagnosing Image-based Cross-View Human-Object Understanding via Single-View Sufficiency and Multi-View Necessity

model-releasesarxiv-cs-cv

arXiv:2606.25634v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in single-image perception, yet their ability to reason about complex cross-view