Search: “reasoning”

CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes

arXiv:2404.01299v3 Announce Type: replace-cross Abstract: Causal video question answering (QA) has garnered increasing interest, yet existing datasets often lack depth in causal reasoning. To address

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Research

CSB: A Counting and Sampling tool for Bit-vectors

DGX agent

arXiv:2607.04142v1 Announce Type: cross Abstract: Satisfiability modulo theory (SMT) solvers have significantly advanced automated reasoning due to their effectiveness in solving problems across vario

researcharxiv-cs-ai

7 Jul 2026

Diversity-aware View Partitioning for Scalable VGGT

arXiv:2607.01885v2 Announce Type: replace Abstract: Geometry transformers such as VGGT achieve strong performance by jointly reasoning over multiple views with global attention. However, scaling them

researcharxiv-cs-cv

Do Medical Vision Language Models Actually See? A Counterfactual Grounding Framework and Hard-Negative Contrastive Training for Visually-Reliant Medical VLMs

model-releasesarxiv-cs-cv

arXiv:2607.03647v1 Announce Type: new Abstract: Large vision language models (VLMs) report strong accuracy on medical question-answering, yet it remains unclear whether they reason from visual evidenc

Don't Wait to Reply: Towards Responsive yet Thoughtful Dialogue through Proactive Thinking

arXiv:2607.03093v1 Announce Type: cross Abstract: Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks. However, its reactive nature, where reasoning i

dOPSD: On-Policy Self-Distillation for Diffusion Language Models

arXiv:2607.04428v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising a masked sequence, offering a parallel alternative to autoregressive mo

FM-ChangeNet: Learning Change through Pathwise Feature Transport

arXiv:2607.04750v1 Announce Type: new Abstract: We present FM-ChangeNet, a pathwise-supervised framework for change detection that reformulates bi-temporal reasoning as continuous transport in feature

FormalRx: Rectify and eXamine Semantic Failures in Autoformalization

model-releasesarxiv-cs-cl

arXiv:2607.04655v1 Announce Type: new Abstract: The veracious semantic alignment in autoformalization is significant for formal mathematical reasoning. However, existing evaluations provide only opaqu

Heaviside Continuity of Rolling Coefficients for Eliminating Epistemic Entropy in Large Language Models

arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro

HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control

arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r

HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis

arXiv:2603.01121v2 Announce Type: replace Abstract: While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable c

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

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

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

Latent Programming Horizons in Coding Agents

arXiv:2607.05188v1 Announce Type: new Abstract: A coding agent solving a software-engineering task spends dozens of steps reasoning, editing code, and running tests, yet little is known about what the

agentsarxiv-cs-lg

Learning When to Attend: Conditional Memory Access for Long-Context LLMs

model-releasesarxiv-cs-cl

arXiv:2603.17484v2 Announce Type: replace Abstract: Language models struggle to generalize beyond pretraining context lengths, limiting long-horizon reasoning and retrieval. Continued pretraining on l

Lipschitz-Based Robustness Certification Under Floating-Point Execution

arXiv:2603.13334v4 Announce Type: replace-cross Abstract: Lipschitz-based robustness certification bounds a network's sensitivity through concrete numerical computation rather than symbolic reasoning,

researcharxiv-cs-cv

On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models

arXiv:2607.04332v1 Announce Type: new Abstract: In this paper, we consider the setting where large language models (LLMs) are trained using reinforcement learning (RL) to simultaneously improve reason

researcharxiv-cs-lg

Programming over Thinking: Efficient and Robust Multi-Constraint Planning

arXiv:2601.09097v3 Announce Type: replace Abstract: Multi-constraint planning involves identifying, evaluating, and refining candidate plans while satisfying multiple, potentially conflicting constrai

Q-TriM: Question-Guided Tri-Modal Attention for Audio-Visual Question Answering

arXiv:2607.03825v1 Announce Type: cross Abstract: Audio-Visual Question Answering (AVQA) extends classical VQA by requiring joint reasoning over video and synchronized audio. However, many AVQA system

Report: 83% of organizations need to upgrade their infrastructure to support agentic AI

model-releasesgoogle-cloud-ai

For years, enterprise AI has been synonymous with conversational AI — the customer service bots and digital assistants we interact with every day. But today, the market has shifted. We’ve officially m

Responsibility Distribution Estimation in Ego-View Accident Videos with Multimodal Large Language Models

arXiv:2607.03591v1 Announce Type: cross Abstract: Recent studies on multimodal traffic accident understanding have mainly relied on infrastructure-camera footage, satellite imagery, or structured cras

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration

arXiv:2509.10656v2 Announce Type: replace-cross Abstract: For groups of autonomous agents to achieve a particular goal, they must engage in coordination and long-horizon reasoning. Rather than relying

Tutorials

Show Me Examples: Inferring Visual Concepts from Image Sets

arXiv:2607.02402v2 Announce Type: replace Abstract: Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, curren

tutorialsarxiv-cs-cv

StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models

arXiv:2603.20659v2 Announce Type: replace Abstract: Large scale pre-training on text and image data along with diverse robot demonstrations has helped Vision Language Action models (VLAs) to generaliz

safetyarxiv-cs-ro

Storage gets promoted in the agentic AI era

The year 2026 could be remembered as the moment when storage technology received a massive promotion. The reason is that the current transition from simple chatbots to agentic AI systems has raised th

agentssiliconangle

The Language of Bargaining: Linguistic Effects in LLM Negotiations

arXiv:2601.04387v2 Announce Type: replace Abstract: Negotiation is a core component of social intelligence, requiring agents to balance strategic reasoning, cooperation, and social norms. Recent work

Tutorials

Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training

arXiv:2607.04969v1 Announce Type: cross Abstract: The training paradigm of large language models has shifted from traditional one-pass training to multi-epoch training, as reasonable reuse of limited

tutorialsarxiv-cs-cl

Weak-to-Strong Generalization via Direct On-Policy Distillation

arXiv:2607.05394v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on ev

WorldBagel: Uncovering the Power of Unified Multimodal Models for Vision-Language-Action-World Modeling

model-releasesarxiv-cs-cv

arXiv:2607.03461v1 Announce Type: new Abstract: World models aim to capture environment dynamics in ways that support perception, reasoning, and action, and have recently become a central direction in

Industry

Automatically redact PII in images with Amazon Nova

In this post, we present a multi-step pipeline directed by Amazon Nova, which uses its contextual vision reasoning to coordinate complementary tools, including Meta’s open-source Segment Anything Mode

industryaws-ml-blog

6 Jul 2026

Local Ai

b9870

local-aillama-cpp-releases

b9870 is a llama.cpp release dated July 3, 2026 , which includes fixes for StepFun parser chat handling to address long reasoning loops . The release provides pre-built binaries for multiple platforms

CoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation

arXiv:2607.02222v1 Announce Type: cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decompositio

Don't Let Gains FADE: Breaking Down Policy Gradient Weights in RL

arXiv:2607.01490v1 Announce Type: cross Abstract: Reinforcement learning post-training dramatically improves LLM reasoning, but suffers from training instability and diversity collapse. Advantage func

Hardware-Enforced Semantic Coordination for Safety-Critical Real-Time Autonomous Systems

arXiv:2607.02376v1 Announce Type: new Abstract: Recent advances in agentic AI are producing increasingly complex autonomous systems that integrate large language models, world models, optimization eng

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer

arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learnin

NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy

model-releasesarxiv-cs-ro

arXiv:2607.02277v1 Announce Type: new Abstract: Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches ofte

Applications

PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations

arXiv:2607.01306v1 Announce Type: new Abstract: Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many

applicationsarxiv-cs-ai

Playing 20 Question Game with Policy-Based Reinforcement Learning

arXiv:1808.07645v5 Announce Type: replace-cross Abstract: The 20 Questions (Q20) game is a well known game which encourages deductive reasoning and creativity. In the game, the answerer first thinks o

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model

arXiv:2607.01595v1 Announce Type: new Abstract: As the scale and complexity of cloud-based AI systems continue to escalate, ensuring service reliability through rapid fault detection and adaptive reco

Scaling with Confidence: Calibrating Confidence of LLMs for Adaptive Test Time Scaling

arXiv:2607.01612v1 Announce Type: new Abstract: Training large language models (LLMs) with reinforcement learning (RL) has significantly advanced their performance on reasoning and question-answering

AlgoBench: Benchmarking Algorithmic Adaptation in Code Generation

arXiv:2607.00062v1 Announce Type: cross Abstract: High pass rates on established programming benchmarks such as HumanEval and LiveCodeBench do not always show whether a model can reason about algorith

GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity

arXiv:2607.00152v1 Announce Type: cross Abstract: Three of the most popular methods for training language models to reason look like three different tricks. They are not. All three adjust a single num

GryphOne: Symbol-Aware Masked Diffusion for Structural Refinement in Offline Handwritten Mathematical Expression Recognition

model-releasesarxiv-cs-cv

arXiv:2602.03370v2 Announce Type: replace Abstract: Handwritten mathematical expression recognition (HMER) requires reasoning over diverse symbols and structures, yet autoregressive models struggle wi

NeuroFilter: Activation-Based Guardrails for Privacy-Conscious LLM Agents

arXiv:2601.14660v2 Announce Type: replace-cross Abstract: Agentic Large Language Models (LLMs) are models able to reason, plan, and execute tools over unstructured data. These abilities are enabling t

PanoGrounder: Bridging 2D and 3D with Panoramic Scene Representations for VLM-based 3D Visual Grounding

arXiv:2512.20907v2 Announce Type: replace Abstract: 3D Visual Grounding (3DVG) is a critical bridge from vision-language perception to robotics, requiring both language understanding and 3D scene reas

researcharxiv-cs-cv

Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets

arXiv:2607.00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, whic

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning

model-releasesarxiv-cs-cl

arXiv:2607.00465v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely extensively on Visual Instruction Tuning (VIT) to elicit their multimodal reasoning capabilities. However, w