Search: “framework”

Steering the Noise: Turning Random Perturbations into Effective Descent for Memory-Efficient LLM Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2601.04710v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) achieves strong performance but is often limited by the memory overhead of backpropagation. Zeroth-order (Z

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SVoT: State-aware Visualization-of-Thought for Spatial Reasoning via Reinforcement Learning

DGX agent

arXiv:2606.11770v1 Announce Type: new Abstract: Spatial reasoning remains a challenge for Multimodal Large Language Models (MLLMs), as it requires reliable multi-hop inference over both intermediate s

safetyarxiv-cs-ai

11 Jun 2026

SwiftCTS: Fast Cross-Design Prediction and Pareto Optimization of Clock Tree Metrics via Few-Shot Calibration

model-releasesarxiv-cs-lg

arXiv:2606.11348v1 Announce Type: new Abstract: Clock Tree Synthesis (CTS) is a computationally expensive stage in the physical design flow, requiring iterative EDA tool invocations to navigate a vast

T2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking

arXiv:2606.11698v1 Announce Type: cross Abstract: Model watermarking safeguards AI model intellectual property by embedding distinctive knowledge that induces unique behavioral signatures. The primary

TacCoRL: Integrating Tactile Feedback into VLA via Simulation

arXiv:2606.11743v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often mis

safetyarxiv-cs-lg

Applications

TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning

arXiv:2606.11640v1 Announce Type: cross Abstract: Few-shot tabular learning provides a cost-effective approach for real-world applications where annotation is costly and collecting sufficient samples

applicationsarxiv-cs-ai

Task-Aware Structured Memory for Dynamic Multi-modal In-Context Learning

arXiv:2606.11853v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) depend on in-context learning (ICL) for rapid task adaptation, but their scalability is severely limited by

TextHOI-3D: Text-to-3D Hand-Object Interaction via Discrete Multi-View Generation and Joint Mesh Optimization

arXiv:2606.11805v1 Announce Type: cross Abstract: Text-conditioned 3D generation has progressed rapidly for images and isolated objects, but producing a hand-object mesh remains challenging: the outpu

The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning

arXiv:2606.11918v1 Announce Type: new Abstract: Current Large Reasoning Models (LRMs) exhibit remarkable general capabilities but significantly underperform in spatial reasoning tasks. Existing approa

Agents

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes

arXiv:2606.11470v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved strong performance across natural language processing tasks, yet reliable reasoning remains an open challenge

agentsarxiv-cs-cl

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models

model-releasesarxiv-cs-lg

arXiv:2606.11625v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) are increasingly explored as predictive experts within emerging agentic time-series systems. However, TSFMs exhibi

To Intervene or Not: Guiding Inference-time Alignment with Probabilistic Model Blending

arXiv:2606.11201v1 Announce Type: cross Abstract: The wide deployment of LLMs has made model alignment necessary to make newly trained models safely and effectively respond to user instructions. Among

Tutorials

TopoCap: Learning Topology-Agnostic Motion Priors for Monocular Video-to-Animation

arXiv:2606.12153v1 Announce Type: new Abstract: The explosion of generative 3D assets has created a massive demand for animation, yet current motion capture methods remain brittle, restricted to speci

tutorialsarxiv-cs-cv

TouchThinker: Scaling Tactile Commonsense Reasoning to the Open World with Large-scale Data and Action-aware Representation

arXiv:2606.11637v1 Announce Type: new Abstract: Touch is a key modality for embodied agents to understand the physical world. Although recent work has incorporated tactile signals into language system

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement

arXiv:2606.11926v1 Announce Type: cross Abstract: Scientific progress depends on a repeated loop of exploration, experimentation, and abstraction. Researchers test candidate directions, interpret the

Towards a Bridge Layer Between Bibliographic and Formalized Mathematical Knowledge

arXiv:2606.11430v1 Announce Type: cross Abstract: Mathematical knowledge is split between bibliographic databases (e.g., MathSciNet, zbMATH Open) and formal proof libraries (e.g., Lean mathlib), preve

Towards Conditional Feature Alignment for Cross-Domain Counting

arXiv:2506.17137v3 Announce Type: replace Abstract: Object counting models often degrade under cross-domain deployment because density composition varies across domains and is itself task-relevant. St

safetyarxiv-cs-cv

Towards Deep Learning Surrogate for the Forward Problem in Electrocardiology: A Scalable Alternative to Physics-Based Models

arXiv:2512.13765v2 Announce Type: replace-cross Abstract: The forward problem in electrocardiology, computing body surface potentials from cardiac electrical activity, is traditionally solved using ph

Agents

TreeSeeker: Tree-Structured Trial, Error, and Return in Deep Search

arXiv:2606.11662v1 Announce Type: new Abstract: Deep search requires agents to answer complex questions through multi-step web search, browsing, evidence comparison, and synthesis. A central challenge

agentsarxiv-cs-ai

Applications

Unifying Learning Dynamics and Generalization in Transformers Scaling Law

arXiv:2512.22088v3 Announce Type: replace-cross Abstract: The scaling law, a cornerstone of Large Language Model (LLM) development, predicts improvements in model performance with increasing computati

applicationsarxiv-cs-ai

UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning

arXiv:2606.12372v1 Announce Type: cross Abstract: Human-in-the-loop reinforcement learning (HiL-RL) has emerged as an effective paradigm for real-world robotic manipulation, enabling online policy imp

safetyarxiv-cs-lg

UniReason-Med: A Shared Grounded Reasoning Interface for 2D-to-3D Transfer in Medical VQA

arXiv:2606.11740v1 Announce Type: cross Abstract: We study whether grounded reasoning supervision from abundant 2D medical images can improve 3D medical VQA when both input types are aligned through a

safetyarxiv-cs-cl

Vector Quantized Latent Concepts: A Scalable Alternative to Clustering-Based Concept Discovery

arXiv:2602.02726v2 Announce Type: replace-cross Abstract: Large language models (LLMs) encode rich semantic information in their hidden states, yet it remains difficult to understand what information

researcharxiv-cs-cl

Verifiable Environments Are LEGO Bricks: Recursive Composition for Reasoning Generalization

model-releasesarxiv-cs-cl

arXiv:2606.12373v1 Announce Type: new Abstract: Reinforcement Learning (RL) with verifiable environments has emerged as a powerful approach for enhancing the reasoning capabilities of Large Language M

VICX: Generalizable Robot Manipulation via Video Generation and In-Context Operator Network

model-releasesarxiv-cs-ro

arXiv:2606.12028v1 Announce Type: new Abstract: Generalizable robot manipulation requires not only task-level reasoning over unseen scenes, but also reliable grounding of visual plans into embodiment-

ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation

arXiv:2606.12023v1 Announce Type: new Abstract: Vision Transformers (ViTs) have gained significant attention in computer vision and shown strong potential for face recognition (FR). However, their hig

safetyarxiv-cs-cv

VL-DINO: Leveraging CLIP Vision-Language Knowledge for Open-Vocabulary Object Detectio

model-releasesarxiv-cs-cv

arXiv:2606.11546v1 Announce Type: new Abstract: Vision-language models like CLIP can provide rich semantic priors for open-vocabulary object detection. However, jointly integrating both textual and vi

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models

arXiv:2606.12263v1 Announce Type: new Abstract: While Latent Diffusion Models (LDMs) have revolutionized visual synthesis, they are increasingly exploited for unauthorized mimicry of individuals. Exis

researcharxiv-cs-cv

When Generic Prompt Improvements Hurt: Evaluation-Driven Iteration for LLM Applications

arXiv:2601.22025v2 Announce Type: replace-cross Abstract: Evaluating Large Language Model (LLM) applications differs from conventional software testing because outputs are probabilistic, semantically

When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines

arXiv:2606.11265v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate downstream model outputs through malicious kno

When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?

arXiv:2510.02660v2 Announce Type: replace-cross Abstract: When researchers claim AI systems possess ToM or mental models, they are fundamentally discussing behavioral predictions and bias corrections

World Model Self-Distillation: Training World Models to Solve General Tasks

model-releasesarxiv-cs-cv

arXiv:2606.12072v1 Announce Type: new Abstract: Pretrained video generators are promising visual world models that exhibit emergent task-solving abilities; however, their reliance on detailed textual

World Pilot: Steering Vision-Language-Action Models with World-Action Priors

model-releasesarxiv-cs-ro

arXiv:2606.12403v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit semantic grounding from large-scale pretraining and perform competently across in-distribution manipulation

XPR: An Extensible Cross-Platform Point-Based Differentiable Renderer

arXiv:2606.11529v1 Announce Type: cross Abstract: Point-based differentiable rendering underpins modern 3D reconstruction, novel-view synthesis, and learning-based graphics pipelines, but developing n

researcharxiv-cs-cv

A fine-grained attention and geometric correspondence model for musculoskeletal risk classification in athletes using multimodal visual and skeletal features

arXiv:2509.05913v3 Announce Type: replace Abstract: Musculoskeletal disorders pose significant risks to athletes, and early risk assessment is essential for prevention. However, most existing methods

safetyarxiv-cs-cv

A History-Aware Visually Grounded Critic for Computer Use Agents

arXiv:2606.11078v1 Announce Type: new Abstract: Various test-time interventions for Computer Use Agents (CUAs), including critic models, have been developed to improve performance through pre-executio

A Practical Recipe Towards Improving Sim-and-Real Correlation for VLA Evaluation

arXiv:2606.10366v1 Announce Type: cross Abstract: Simulation has become an essential tool for evaluating and improving vision-language-action (VLA) policies, offering scalable, reproducible, and contr

A Spiking Neural Architecture for Coordinating Arm and Locomotor Control

arXiv:2606.11034v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) coupled with neuromorphic hardware offer energy-efficient solutions for humanoid robot control. However, existing SNN-bas

researcharxiv-cs-ro

A Systematic Approach for Selecting Trajectories for Data Augmentation

arXiv:2606.10938v1 Announce Type: new Abstract: Trajectory data augmentation is a promising approach to mitigate data scarcity in machine learning applications, but its utility has been limited by the

researcharxiv-cs-lg

Tutorials

A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

arXiv:2606.11189v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) typically maximizes the likelihood of every token in a demonstrated trajectory. However, an observed token can be non-uni

tutorialsarxiv-cs-ai

Accelerating SAV-based optimization via randomized low-rank Hessian approximation

arXiv:2606.10562v1 Announce Type: cross Abstract: We propose a new optimization method, the Nystrom-enhanced relaxed scalar auxiliary variable method (N-RSAV), which incorporates curvature information

researcharxiv-cs-lg

Act on What You See: Unlocking Safe Social Navigation in Vision-Language-Action Models

arXiv:2606.10495v1 Announce Type: new Abstract: Safe social navigation requires robots to distinguish people from ordinary obstacles and to react before danger becomes imminent. We show that pretraine

safetyarxiv-cs-ro

Agents

ActiveMem: Distributed Active Memory for Long-Horizon LLM Reasoning

arXiv:2606.10532v1 Announce Type: new Abstract: Memory is essential for enabling large language model (LLM) agents to handle long-horizon reasoning tasks. Existing memory mechanisms are largely centra

agentsarxiv-cs-ai

Tutorials

Aesthetic Perspectives in Information Systems Research: A Hermeneutic Analysis

arXiv:2606.09839v1 Announce Type: cross Abstract: How might implicit aesthetic perspectives shape what Information Systems (IS) scholarship recognises as worthy of study (or not)? In this hermeneutic

tutorialsarxiv-cs-ai

Algorithmic and Minimax Complexities in Kernel Bandits

arXiv:2606.11171v1 Announce Type: new Abstract: Gaussian-process upper confidence bound (GP-UCB) and decision-estimation-coefficient (DEC) methods may appear, at first sight, to belong to different th

researcharxiv-cs-lg

Alignment Defends LLMs from Property Inference Attacks

arXiv:2606.10217v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly fine-tuned on domain-specific datasets that may contain sensitive, dataset-level properties. Recent work h

safetyarxiv-cs-lg

Applications

AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning

arXiv:2606.10927v1 Announce Type: new Abstract: Lifelong embodied navigation in dynamic environments requires robots to form persistent scene understanding from fragmentary observations, which remains

applicationsarxiv-cs-ro

Local Ai

AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning

arXiv:2602.13807v2 Announce Type: replace Abstract: Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support rel

local-aiarxiv-cs-lg