Search: “framework”

arXiv:2607.28855v1 Announce Type: cross Abstract: Dense 3D sensors in various real-world fields produce point clouds that are geometrically redundant for real-time processing. In this paper, we propos

applicationsarxiv-cs-cv

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Local Ai

LightningRL: Breaking the Accuracy-Parallelism Trade-off of Block-wise dLLMs via Reinforcement Learning

DGX agent

arXiv:2603.13319v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising paradigm for parallel token generation, with block-wise variants garnering signi

local-aiarxiv-cs-lg

3 Aug 2026

Memory Provenance Laundering in LLM Agents: A Non-Amplification Firewall for Persistent Memory

arXiv:2607.29167v1 Announce Type: cross Abstract: Long-term memory lets large language model(LLM) agents reuse prior preferences and work flows, but it also turns untrusted observations into persisten

ModelEquivBench: Certifying Multi-Relational Evaluation of LLM-Generated Optimization Models

arXiv:2607.29431v1 Announce Type: new Abstract: Large language models increasingly generate optimization models from natural language, but existing evaluation often reduces a generated model and its g

OASIS: Occlusion-aware Single-image Hand Avatar Reconstruction via 3D Gaussian Splatting

arXiv:2607.29633v1 Announce Type: new Abstract: Single-image 3D hand avatar reconstruction is fundamentally ill-posed and particularly challenging due to limited visual evidence under severe self-occl

Local Ai

OnlineCache: Learning Dynamic Caching Policies with Error Correction for Efficient Diffusion Inference

arXiv:2607.29398v1 Announce Type: new Abstract: Diffusion models have revolutionized generative tasks but incur high latency due to iterative denoising. While cache-based strategies accelerate inferen

local-aiarxiv-cs-lg

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und

PiDDM: Physics-Informed Differentiable Degradation Modeling for Lithium-Ion Battery State-of-Health Prediction

arXiv:2607.29095v1 Announce Type: new Abstract: Accurate prediction of lithium-ion battery state of health (SOH) is essential for reliable energy storage operation. However, purely data-driven models

researcharxiv-cs-lg

QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models

arXiv:2607.29445v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering

Rethinking Detection Calibration: A Coordinate and Direction Perspective

arXiv:2607.29040v1 Announce Type: new Abstract: Deep learning based object detectors require trustworthiness beyond competitive detection performance, but deep neural networks are prone to overconfide

safetyarxiv-cs-cv

Shall We Play a Game? Language Models for Open-ended Wargames

arXiv:2509.17192v3 Announce Type: replace Abstract: LLM-based social simulations can make a generated transcript look like a single behavioral signal, but the model behind that transcript may be doing

Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens

arXiv:2607.29363v1 Announce Type: cross Abstract: Balancing sequence length, representational capacity, and long-horizon stability is a central problem in autoregressive (AR) speech and audio generati

Hardware

Studying quantization trade-offs for efficient inference deployment in machine translation

arXiv:2607.29397v1 Announce Type: new Abstract: Deploying large language models in realistic server environments poses challenges, as the system needs to provide high-quality responses with low latenc

hardwarearxiv-cs-cl

The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection

arXiv:2607.29541v1 Announce Type: new Abstract: In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while benefici

safetyarxiv-cs-cv

The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs

model-releasesarxiv-cs-lg

arXiv:2607.29601v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) commonly adapts large language models using a single shared Low-Rank Adapter (LoRA). This shared optimization spa

Tokenizer-Agnostic Engram Module

model-releasesarxiv-cs-cl

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

arXiv:2607.28640v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) should generate consistent responses given semantically equivalent inputs across modalities. However, we observ

researcharxiv-cs-cl

Applications

Towards Automated Initial Probe Placement in Transthoracic Teleultrasound Using Human Mesh and Skeleton Recovery

arXiv:2603.11257v2 Announce Type: replace Abstract: Cardiac and lung ultrasound are technically demanding because operators must identify patient-specific intercostal acoustic windows and then navigat

applicationsarxiv-cs-cv

Training-Free Entity-Level Few-Shot Segmentation of Remote Sensing Images with Advection Refinement

arXiv:2607.29278v1 Announce Type: new Abstract: Existing cross-domain few-shot segmentation approaches suffer from high training costs due to source-domain episodic training and pixel-wise dense predi

ViSAGE: Constructing Self-Correcting Memories for Long-Form Video Understanding

arXiv:2607.28678v1 Announce Type: new Abstract: Multimodal agents operating in long-horizon environments must build and continually update multimedia memories to support entity-consistent, temporally

When Model Priors Conflict with Visual Evidence: Mitigating Commonsense-Driven Hallucinations by Selective Prior Calibration

arXiv:2607.29240v1 Announce Type: cross Abstract: In vision--language models, commonsense-driven hallucination (CDH) occurs when a model's commonsense prior overrides clear visual evidence of an atypi

Why It Hurts: Identifying the Drivers of Negative Thoughts in Emotional Support Conversations

arXiv:2607.28648v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for emotional support tasks, such as negative thought reframing. This task relies on modifying cogn

AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes

model-releasesarxiv-cs-cl

arXiv:2607.27393v1 Announce Type: new Abstract: Hateful memes are a growing form of multimodal online harm, where hostile intent is often conveyed through the joint interpretation of images, text, cul

Agents

AI as Friction for Reflection Support in Ideation

arXiv:2607.26827v1 Announce Type: cross Abstract: Generative AI tools for creative work tend to be designed around the goal of removing friction, on the assumption that smoother iteration and faster o

agentsarxiv-cs-ai

AI Security Priorities: A Field-Wide Agenda

arXiv:2607.26069v1 Announce Type: cross Abstract: As AI systems are rapidly integrated into critical economic, governmental, and national security functions, the gap between AI adoption and AI securit

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

arXiv:2607.28617v1 Announce Type: cross Abstract: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout com

researcharxiv-cs-cl

APO: Unsupervised Atomic Policy Optimization for 3D Structure Prediction of Atomic Systems

arXiv:2607.28553v1 Announce Type: new Abstract: Predicting the 3D structures of atomic systems is fundamental to advancing material science and drug discovery. While flow-matching models (, FlowDPO) h

safetyarxiv-cs-lg

Tutorials

Backbone-Agnostic Stochastic Perturbation Learning for End-to-End Real-World Image Dehazing

arXiv:2607.11623v3 Announce Type: replace Abstract: Real-world paired image dehazing remains challenging because haze degradation is spatially non-uniform, illumination-dependent, and physically ambig

tutorialsarxiv-cs-cv

Agents

Belief Coevolution in a Social Network of Generalist and Specialist Large Language Models

arXiv:2607.27512v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in multi-agent environments. However, the processes by which beliefs form and propagate among int

agentsarxiv-cs-cl

Beyond Binary Rewards: A Comparative Study of Reward Design for Reinforcement Unlearning

model-releasesarxiv-cs-lg

arXiv:2607.27968v1 Announce Type: new Abstract: Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privac

Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures

arXiv:2607.28007v1 Announce Type: new Abstract: Pathology foundation models (FMs) are models trained on vast amounts of typically unlabeled data and have been shown to yield regularized latent spaces

Beyond Feeling Better: Capability-Sustaining Emotional Dialogue as a Longitudinal Research Paradigm

arXiv:2607.27851v1 Announce Type: new Abstract: Emotional dialogue research includes two influential strategy traditions. Empathetic dialogue prioritizes understanding a speaker's emotional experience

safetyarxiv-cs-cl

ChronoMem: Version Control and Semantic Rollback for Large Language Model Agent Memory

model-releasesarxiv-cs-cl

arXiv:2607.27773v1 Announce Type: new Abstract: LLM agents increasingly rely on long-term memory to support multi-session interaction and personalization. However, existing agent memory systems are de

Comparison of a Parametric Physics-Informed Neural Network and a Tensorial Reduced-Order Model for the Shallow-Water Dam-Break Problem

model-releasesarxiv-cs-lg

arXiv:2607.27433v1 Announce Type: cross Abstract: We develop two parametric data-driven reduced models: a physics-informed neural network (PINN) and a non-intrusive tensorial reduced-order model (TROM

Compliance2LoRA: On-Demand Safety Alignment on Arbitrary Policy Subsets via Hypernetwork-Generated LoRA Adapters

arXiv:2607.27594v1 Announce Type: new Abstract: Post-training alignment in large reasoning models (LRMs) has significantly improved their adaptability to diverse safety compliance settings. However, a

safetyarxiv-cs-lg

Compression-Based Behavioral Similarity for Open-World Sybil Discovery on Ethereum

arXiv:2607.27370v1 Announce Type: new Abstract: Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sy

researcharxiv-cs-lg

Eco3S: Complex Socio-Economic System Simulation via Agent-Based Models

arXiv:2607.26588v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has renewed interest in agent-based modeling (ABM). However, current LLM-based ABM research faces

Endo-NeRF++: Uncertainty-Aware Neural Rendering with Multi-Resolution Hash Encoding for Dynamic Surgical Scene Reconstruction

arXiv:2607.27825v1 Announce Type: cross Abstract: Reconstructing dynamic surgical scenes is crucial for robot-assisted minimally invasive surgery; however, it continues to be difficult because of tiss

Evidence-Ledger Adjudication for Claim-Evidence Traceability

arXiv:2607.26512v1 Announce Type: new Abstract: AI agents can draft claims faster than authors can check whether the cited or retrieved evidence supports them. We study evidence-ledger adjudication: a

Expanding Data-Agnostic Pivotal Instances Selection Models with Proximity Trees and Ensemble Learning

arXiv:2607.27522v1 Announce Type: new Abstract: As decision-making processes grow more complex, machine learning tools have become essential for tackling business and societal challenges. However, man

researcharxiv-cs-lg

Agents

FaithEyes: Towards Faithful Tool Use via Multi-Agent Process-Image Verification

arXiv:2607.28225v1 Announce Type: new Abstract: Agentic vision-language models (VLMs), which interleave textual reasoning with explicit tool calls such as cropping and code-based image manipulation, h

agentsarxiv-cs-cv

FDDWAN: A Frequency-Decoupled Diffusion Network for Watermarking Attack

arXiv:2607.27800v1 Announce Type: new Abstract: Existing invisible watermark removal methods often struggle to accurately capture the watermark-bearing features, leading to an unfavorable trade-off be

Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution

arXiv:2607.28196v1 Announce Type: new Abstract: Practitioners accept a compressed language model once it clears a stack of data-cheap quality guards: perplexity within a small factor of the original,

safetyarxiv-cs-cl

FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning

arXiv:2607.28127v1 Announce Type: new Abstract: Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs). H

researcharxiv-cs-cl

Local Ai

First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on f

local-aiarxiv-cs-lg

FlexiGrad: Adaptive Gradient Modulation for Hierarchical Fine-Grained Classification

model-releasesarxiv-cs-cv

arXiv:2607.17563v2 Announce Type: replace Abstract: Many fine-grained recognition tasks contain hierarchical labels such as order, family and species. Although this supervision should be beneficial, j

Tutorials

FootprintNet: State-Transition-Guided Dynamic Footprint Learning for Multi-temporal Remote Sensing Change Detection

arXiv:2607.27969v1 Announce Type: new Abstract: Despite substantial progress in remote sensing multi-temporal change detection (MTCD), most existing MTCD methods still represent the dynamic process at

tutorialsarxiv-cs-cv

Foundation-Model Earth Representations Enable Regional-Scale Forest Aboveground Biomass Monitoring Across the Northeastern United States

arXiv:2607.27217v1 Announce Type: cross Abstract: Forest aboveground biomass (AGB) is a critical indicator of ecosystem productivity and terrestrial carbon storage, yet regional carbon monitoring rema

safetyarxiv-cs-lg