Search: “reasoning”

GVC-Seg: Training-Free 3D Instance Segmentation via Geometric Visual Correspondence

arXiv:2606.08014v1 Announce Type: cross Abstract: Accurate 3D instance segmentation in point cloud data is critical for machine vision applications. Recent advancements leverage multiple pre-trained f

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Model Releases

How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions

DGX agent

arXiv:2606.08051v1 Announce Type: new Abstract: Financial transaction processing requires extracting structured merchant information from noisy, abbreviated bank transaction strings at scale. Our curr

model-releasesarxiv-cs-ai

9 Jun 2026

Applications

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation

arXiv:2509.10334v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) have recently achieved strong results in semantic segmentation, yet their deployment on resource-constrained device

applicationsarxiv-cs-ai

InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs

arXiv:2606.08601v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently demonstrated impressive potential for time series forecasting. However, existing methods predominantly rely o

Instrumented data for causal scientific machine learning

arXiv:2606.07865v1 Announce Type: cross Abstract: Scientific machine learning is limited less by model size than by the data it is trained on. Observational data records what happened but not why; tem

Investigating the Histogram Loss in Regression

arXiv:2402.13425v3 Announce Type: replace-cross Abstract: It is becoming increasingly common in regression to train neural networks that model the entire distribution even if only the mean is required

Joint Structural Pruning and Mixed-Precision Quantization for LLM Compression

arXiv:2606.07819v1 Announce Type: new Abstract: Recently, the efficiency of Large Language Models (LLMs) deployment has become a critical concern in practical applications. While post-training quantiz

KPGrasp: Scalable Keypoint Flow Matching for Dexterous Grasp Generation

model-releasesarxiv-cs-ro

arXiv:2606.09314v1 Announce Type: new Abstract: Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly

Language as a Sensor: Calibrated Spatial Belief Estimation in 3D Scenes from Natural Language

model-releasesarxiv-cs-ro

arXiv:2606.08666v1 Announce Type: new Abstract: Robots deployed in human-centric environments routinely receive natural-language descriptions of spatial information ('I left my backpack on the table')

Applications

Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook

arXiv:2310.10196v3 Announce Type: replace-cross Abstract: Temporal data, including time series and spatio-temporal data, are pervasive in real-world applications. Generated in massive volumes by physi

applicationsarxiv-cs-ai

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation

arXiv:2606.09131v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone designed for unimodal text modeling, and apply the sa

LCAM: A Framework for Diagnosing Interactional Alignment Failures in Con-versational AI

arXiv:2606.08131v1 Announce Type: cross Abstract: Conversational AI is increasingly used for advice, interpretation, reassurance, and decision support in contexts where users may be vulnerable, uncert

MAVIS: Multi-Agent Video Retrieval via Structured Video Understanding

arXiv:2606.09641v1 Announce Type: new Abstract: The dominant paradigm in video retrieval relies on embedding-based full-corpus scanning, which suffers from inherent computational inefficiency and the

agentsarxiv-cs-cv

Memory Beyond Recall: A Dual-Process Cognitive Memory System for Self-Evolving LLM Agents

arXiv:2606.09483v1 Announce Type: cross Abstract: Long-term memory for an LLM agent is more than retrieving the right passage at the right time. Current memory systems collapse belief revision, causal

Model-Based Learning of Whittle indices

model-releasesarxiv-cs-lg

arXiv:2511.20397v2 Announce Type: replace Abstract: We present BLINQ, a new model-based algorithm that learns the Whittle indices of an indexable, communicating and unichain Markov Decision Process (M

More Bang for the Buck: Improving the Inference of Large Language Models at a Fixed Budget using Reset and Discard (ReD)

arXiv:2601.21522v2 Announce Type: replace-cross Abstract: The performance of large language models (LLMs) on verifiable tasks is usually measured by pass@k, the probability of answering a question cor

MOSS-Video-Preview: Toward Real-Time Video Understanding via Cross-Attention

arXiv:2606.07639v1 Announce Type: cross Abstract: Video understanding is shifting from the offline paradigm -- taking a fully recorded video as input and producing a single answer after it ends -- tow

Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training

arXiv:2601.03256v2 Announce Type: replace Abstract: We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on pa

safetyarxiv-cs-cv

Observability for Delegated Execution in Agentic AI Systems

arXiv:2606.09692v1 Announce Type: cross Abstract: Delegation-scoped execution is not identifiable from standard observables: audit logs and execution traces can be identical under multiple incompatibl

OmniCap-IF: Benchmarking and Improving Instruction Following Abilities for Omni-Video Captioning

arXiv:2606.08572v1 Announce Type: new Abstract: While Omni-modal Large Language Models (OLLMs) have demonstrated impressive capabilities in jointly processing audio and visual streams, their ability t

Operationalising the Superficial Alignment Hypothesis via Task Complexity

arXiv:2602.15829v2 Announce Type: replace Abstract: The superficial alignment hypothesis (SAH) posits that large language models learn most of their knowledge during pre-training, and that post-traini

Partially Performative Prediction

arXiv:2606.07890v1 Announce Type: new Abstract: Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains. In these settings, deploying a m

researcharxiv-cs-lg

Payoff scaling shapes cooperation in LLM agents across languages

arXiv:2601.19082v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users. Whether they coo

PBSD: Privileged Bayesian Self-Distillation for Long-Horizon Credit Assignment

arXiv:2606.09348v1 Announce Type: new Abstract: Long-horizon agentic tasks pose a fundamental credit assignment challenge for outcome-base reinforcement learning: trajectory-level rewards verify final

Local Ai

PhysAgent: Automating Physics-Based 4D Synthesis via Trajectory-Grounded Multi-Agent Feedback

arXiv:2606.08688v1 Announce Type: cross Abstract: Achieving fully automated, physically plausible 3D motion synthesis is a core objective in graphics and generative AI. However, configuring complex en

local-aiarxiv-cs-cv

Physics-Guided Dual Decoding and Spectral Supervision for Global 3D Hydrometeor Prediction

arXiv:2606.08563v1 Announce Type: new Abstract: While global data-driven models excel at predicting continuous atmospheric variables, three-dimensional hydrometeor forecasting remains challenging due

researcharxiv-cs-lg

Tutorials

Post-training is (Massive) Supervised Learning

arXiv:2606.07527v1 Announce Type: cross Abstract: The prevailing paradigm for training LLMs has evolved to rely on a massive post-training phase consisting of SFT and RL. In this position paper, we ar

tutorialsarxiv-cs-ai

PriFT: Prior-Support Guided Supervised Fine-Tuning

arXiv:2606.09396v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is an efficient approach for downstream task adaptation and often serves as the initialization stage for reinforcement le

Projecting the Emerging Mindset of SWE Agent by Launching a Wild Code Understanding Journey

arXiv:2606.08500v1 Announce Type: cross Abstract: Software engineering agents (SWE agents) increasingly work through tool-mediated trajectories in real repositories, yet their behavior remains difficu

Proxy Reward Internalization and Mechanistic Exploitation: A Learned Precursor to Reward Hacking and Its Generalization

arXiv:2606.09711v1 Announce Type: new Abstract: Reward hacking is usually studied after it becomes visible, once a model earns high proxy reward while failing the intended task. We instead study what

Tutorials

Public Machine Learning Solver Framework for Novices in the Machine Learning Domain

arXiv:2606.08212v1 Announce Type: new Abstract: Solving machine learning problems is complex and typically reserved for experts. Over the past two decades, systems have emerged to support non-experts.

tutorialsarxiv-cs-lg

QueryWeaver: Reliable Multi-Tool Query Execution Planning via LLM-Based Graph Generation

arXiv:2606.08300v1 Announce Type: new Abstract: Many real-world queries over personal data span multiple applications and require structured planning, as individual tools expose only partial informati

agentsarxiv-cs-lg

REFLECT: Intervention-Supported Error Attribution for Silent Failures in LLM Agent Traces

arXiv:2606.09071v1 Announce Type: new Abstract: Large language model (LLM) agents now solve complex tasks through long plan-and-execution traces, yet the ability to locate errors in a completed traces

Reliable to Expressive: A Curriculum for Rubric-Following Safety Judges

arXiv:2606.09165v1 Announce Type: new Abstract: Safety judges are increasingly deployed to evaluate model outputs against evolving criteria, yet recent meta-evaluation work shows they remain brittle u

Tutorials

RGB-S: Image-Aligned Tactile Saliency for Robust Dexterous Manipulation

arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. Ho

tutorialsarxiv-cs-cv

SAGE: Shape-Adapting Gated Experts for Adaptive Histopathology Image Segmentation

arXiv:2511.18493v4 Announce Type: replace-cross Abstract: The significant variability in cell size and shape continues to pose a major obstacle in computer-assisted cancer detection on gigapixel Whole

SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

arXiv:2602.09809v2 Announce Type: replace Abstract: Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorr

See More, Think Deeper: Query-Expanded Visual Evidence and Answer-Clue Guided Reflection for Long Video Understanding

arXiv:2606.09064v1 Announce Type: cross Abstract: Recent advances in Video Large Language Models (Video-LLMs) have enabled performance on long-video understanding tasks. However, existing methods stil

SG-OPD: Sign-Gated On-Policy Distillation via Sign-Consistency Gating and Phased Teacher Sampling

arXiv:2606.09304v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student on its own trajectories with dense per-token supervision from a stronger teacher, and often outperforms

Streaming Interventions: Can Video Large Language Models Correct Mistakes as They Occur?

arXiv:2606.09547v1 Announce Type: new Abstract: Learning everyday skills, like cooking a dish, relies increasingly on instructional media such as online videos. This opens the door to the use of video

Struct-Searcher: Agentic Structural Thinking Advances Multimodal Deep Information Seeking

arXiv:2606.07689v1 Announce Type: new Abstract: Deep research agents have attracted increasing attention for their ability to collect large-scale online information to acquire target knowledge, with r

Structured Neuron Pruning in Deep Neural Networks Using Multi-Armed Bandits

arXiv:2606.07615v1 Announce Type: cross Abstract: Deep neural networks often contain redundant hidden units. Removing individual weights can reduce parameter count, but unstructured sparsity is not al

Structuring agentic AI for HPC code modernization

arXiv:2606.08710v1 Announce Type: cross Abstract: Modernization of legacy scientific codes is often necessary to keep up with the ever-evolving changes in the compute resource ecosystem. Parallelizati

Summarization is Not Dead Yet

arXiv:2606.08000v1 Announce Type: cross Abstract: The progress of large language models (LLMs) has fueled claims that model-generated summaries rival or even surpass human-written references, raising

TheoremBench: Evaluating LLMs on Theorem Proving in Formal Mathematics

arXiv:2606.09450v1 Announce Type: new Abstract: LLMs have recently achieved strong results on formal proving benchmarks. However, existing evaluations remain heavily concentrated on competition-style

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering

arXiv:2411.19504v2 Announce Type: replace Abstract: The advance of large language models (LLMs) has unlocked great opportunities in complex multi-modal data management tasks, particularly in question

Trajectory Geometry of Transformer Representations Across Layers

arXiv:2606.09287v1 Announce Type: new Abstract: Understanding how transformer representations evolve across layers, not merely what they encode, remains an open problem in mechanistic interpretability

researcharxiv-cs-lg

Trajectory-Refined Distillation

arXiv:2606.08432v1 Announce Type: new Abstract: On-policy distillation (OPD) has become a central post-training tool for large language models (LLMs), providing dense per-token teacher supervision alo