Search: “framework”

Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech

arXiv:2607.26236v1 Announce Type: cross Abstract: AI-generated counterspeech offers a scalable and effective strategy to mitigate online toxicity by promoting more constructive dialogue. Yet, existing

researcharxiv-cs-ai

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Model Releases

CoRE-UIR: Prior-guided common and residual experts for efficient all-in-one remote sensing image restoration

DGX agent

arXiv:2607.27898v1 Announce Type: new Abstract: Remote sensing images acquired by unmanned aerial vehicles (UAVs) and satellites are often degraded by adverse weather, illumination variation, and imag

model-releasesarxiv-cs-cv

31 Jul 2026

Creative Transformation in Literary Texts: Modelling Change Across Representational Levels

arXiv:2607.28513v1 Announce Type: new Abstract: Creativity is often framed as the production of novelty, yet many cultural works emerge through transformation of earlier artifacts and not through isol

safetyarxiv-cs-cl

CRMWeaver: Building Powerful Business Agent via Agentic RL and Shared Memories

arXiv:2510.25333v2 Announce Type: replace Abstract: Recent years have witnessed the rapid development of LLM-based agents, which shed light on using language agents to solve complex real-world problem

agentsarxiv-cs-cl

DECODE: Tackling Representation and Decision Degradation in Continual AI-Generated Image Detection

arXiv:2607.27882v1 Announce Type: new Abstract: As generative models continue to evolve, AI-generated image detectors must incrementally adapt to emerging generative domains while preserving knowledge

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Applications

DIPHINE: Diffusion-based Phi-ID Neural Estimator

arXiv:2606.18997v2 Announce Type: replace Abstract: Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly

applicationsarxiv-cs-lg

Divergence Decoding: Training-Free Capability Fusion

arXiv:2607.27248v1 Announce Type: cross Abstract: While large language models excel in reasoning, these generalists often lack knowledge for specialized scientific domains. Conversely, domain models~(

DualAnchor: Preserving Language Priors and Improving Lexical Fidelity in Gloss-Free Sign Language Translation

arXiv:2607.27614v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led sign language translation (SLT), the task of converting sign-language videos into spoken-langua

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Tutorials

Dynamically Scaled Activation Steering

arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat

tutorialsarxiv-cs-lg

ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders

arXiv:2607.27404v1 Announce Type: new Abstract: Existing benchmarks for electrocardiogram foundation models primarily evaluate downstream predictive performance, providing limited insight into whether

EmoFeedback^2: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

arXiv:2511.19982v3 Announce Type: replace Abstract: Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions

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ENCORE: Event-Assisted Complementary Motion Refinement for Learned Video Compression

arXiv:2607.28020v1 Announce Type: new Abstract: Learned video compression relies on accurate temporal modeling to remove redundancy between adjacent frames. However, most existing codecs infer motion

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models

arXiv:2603.05950v2 Announce Type: replace Abstract: Visual token reduction is critical for accelerating Vision-Language Models (VLMs), since visual inputs are represented as token sequences that intro

Even More Deception: Objective Misalignment in Mixed-Motive LLM Multi-Agent Systems

arXiv:2607.26120v1 Announce Type: new Abstract: Large Language Models (LLMs)-powered multi-agent systems are increasingly deployed in mixed-motive environments, where agents operate under asymmetric i

agentsarxiv-cs-ai

Event-Structured Physics-Informed Neural Networks for Differentiable Critical Clearing Boundaries

arXiv:2607.27681v1 Announce Type: new Abstract: Transient-stability assessment determines whether a power system can recover after a disturbance and is therefore essential to preventing generator trip

Expected Survival-Time Bounds for Robust Optimization Over Time under Isotropic Gaussian Dynamics

arXiv:2607.27280v1 Announce Type: cross Abstract: Robust Optimization Over Time (ROOT) is a recent branch of evolutionary dynamic optimization that seeks solutions capable of remaining effective acros

Local Ai

Explaining Image Similarity with Automatically Extracted Concept Activation Vectors

arXiv:2607.28386v1 Announce Type: new Abstract: Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing ex

local-aiarxiv-cs-cv

Hardware

FARI: Robust One-Step Inversion for Watermarking in Diffusion Models

arXiv:2607.26723v1 Announce Type: cross Abstract: Inversion-based watermarking is a promising approach to authenticate diffusion-generated images, yet practical use is bottlenecked by inversion that i

hardwarearxiv-cs-ai

Tutorials

FedOGL: Combating Catastrophic Forgetting in Federated Open-World Multimodal Graph Learning

arXiv:2607.27665v1 Announce Type: new Abstract: Federated graph learning enables collaborative training over decentralized graph data without sharing raw graph information. As such risks evolve, clien

tutorialsarxiv-cs-lg

FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing

model-releasesarxiv-cs-ai

arXiv:2508.02092v3 Announce Type: replace-cross Abstract: Large language models represent significant investments in computation, data, and engineering expertise, making them extraordinarily valuable

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

model-releasesarxiv-cs-cl

arXiv:2607.28568v1 Announce Type: new Abstract: Recursive self-improvement (RSI) requires AI systems that improve the process of building AI (i.e., AI4AI); machine learning engineering (MLE) offers a

FunL2O: LLM-Guided Feature Function Design for Learning to Optimize

arXiv:2607.27389v1 Announce Type: new Abstract: Learning-to-optimize (L2O) methods accelerate repeated optimization by training models to predict solutions, warm starts, branching decisions, or other

GGC: Selective Query Correction for Reliable Text-to-SPARQL Generation

arXiv:2607.28082v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in structured query generation, making them a natural choice for Text-to-SPARQL, whic

researcharxiv-cs-cl

Graph Is the Verifier: Agentic Reinforcement Learning for Interprocedural Vulnerability Detection

arXiv:2607.26656v1 Announce Type: cross Abstract: Real-world vulnerabilities often span multiple functions, yet most learning-based detectors classify each function in isolation: on a sample of real C

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Graph Neural Multilevel Preconditioners for Iterative Solvers

arXiv:2607.28456v1 Announce Type: cross Abstract: Solving large, sparse linear systems is a core task in scientific computing, and efficient iterative solvers rely critically on effective and robust p

GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference

arXiv:2607.27694v1 Announce Type: cross Abstract: Low-bit quantization is essential for efficient LLM inference, and both rotation and fine-grained group quantization have shown individual promise. Ho

Hallucinations Leave a Grounding Signature:Verifier-Guided Decoding for Selective Object Correction

arXiv:2607.27823v1 Announce Type: new Abstract: Large vision-language models (LVLMs) often hallucinate objects that are absent from an image. Despite recent progress, existing mitigation methods still

Harness-G: A Graph-Structured Harness for Search Agents

arXiv:2607.27652v1 Announce Type: new Abstract: Reinforcement learning (RL) search agents commonly model retrieval as free-form natural-language query generation and optimize multi-turn interactions u

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Heterogeneous Ranking in Industrial-Scale Recommender Systems: A Case Study

arXiv:2607.27577v1 Announce Type: cross Abstract: Heterogeneous recommendation feeds present complex challenges that extend beyond those found in highly homogeneous environments (e.g., music-only or v

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IFCMemoryBench: Evaluating Long-Term Memory of LLM-Based Agents in BIM Information Retrieval

model-releasesarxiv-cs-ai

arXiv:2607.26072v1 Announce Type: cross Abstract: Long-term memory is becoming a core capability of LLM-based agents, but existing evaluations largely test conversational recall in open-domain or pers

Improving Item Discoverability in e-Commerce Search via Related Intent Generation

arXiv:2607.27172v1 Announce Type: cross Abstract: Traditional search systems are optimized to retrieve items that strictly match a query, often prioritizing precision over recall. In e-commerce market

researcharxiv-cs-ai

Applications

Information Bottleneck Learning for Faithful Time Series Forecasting Explanations

arXiv:2607.28124v1 Announce Type: new Abstract: As forecasts increasingly drive decisions in fields such as energy, transportation, and healthcare, understanding the historical data behind these predi

applicationsarxiv-cs-lg

It's Not Just More Demos: Counterfactual Action Sensitivity Coverage for Data-Efficient Robust Robot Imitation

arXiv:2607.27261v1 Announce Type: new Abstract: Visuomotor imitation learning has demonstrated success for manipulation tasks. However, the trained policies remain brittle to visual `nuisances', with

safetyarxiv-cs-ro

Learning Color Grading, No Photo Sharing: Federated Aesthetic Preference Learning for Personalized Image Enhancement

model-releasesarxiv-cs-cv

arXiv:2607.27659v1 Announce Type: new Abstract: Personalized image enhancement should reflect individual aesthetic taste, yet learning such preferences commonly depends on private photos and ratings t

LM-GRASP: Instance-Specific Language Models for Combinatorial Construction via Online Imitation Learning

arXiv:2607.28135v1 Announce Type: new Abstract: Machine learning for combinatorial optimization typically relies on neural constructors trained via reinforcement learning on large offline datasets for

MedXplore: Towards Reliable and Unbiased Generalized Category Discovery in Medical Imaging

arXiv:2607.27620v1 Announce Type: new Abstract: Deep learning has shown strong potential in medical image analysis, but most existing methods rely on large-scale annotations and a closed-world assumpt

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Tutorials

MetaRank: Task-Aware Metric Selection for Model Transferability Estimation

arXiv:2511.21007v2 Announce Type: replace Abstract: Selecting an appropriate pre-trained source model is a critical, yet computationally expensive, task in transfer learning. Model Transferability Est

tutorialsarxiv-cs-cv

MMHBench: A Multi-Perspective Benchmark for Mental Health Understanding in Long-Form Videos

model-releasesarxiv-cs-cv

arXiv:2607.27895v1 Announce Type: cross Abstract: Mental health understanding in long-form videos requires nuanced reasoning over observable behavior, interpersonal context, and latent psychological s

Model-Driven Requirements Configuration with Three-Valued Uncertainty Scoring

arXiv:2607.26220v1 Announce Type: cross Abstract: Context: Large Language Models (LLMs) offer natural-language flexibility for automated requirements elicitation but frequently generate structurally i

agentsarxiv-cs-ai

Modeling Decisions in Blockchain Analytics: A Leakage-Aware Evaluation of Tree-Based vs. Sequential Models

arXiv:2607.27350v1 Announce Type: new Abstract: Sybil bots are Ethereum actors that imitate legitimate users to extract airdrop rewards or influence governance. Recent Sybil detection methods increasi

More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility

arXiv:2607.27255v1 Announce Type: cross Abstract: Neural networks increasingly combine data across populations, time periods, and operating conditions to improve generalization. This raises a reliabil

MUL-T: Decoding Spatial Cellular Architecture in Multiplexed Tissue Images

arXiv:2607.28030v1 Announce Type: cross Abstract: Understanding tissue organisation in multiplexed imaging requires modelling both cellular phenotypes and their spatial context. Existing approaches ty

Multi-channel Uplift Policy Learning

arXiv:2607.28182v1 Announce Type: new Abstract: E-commerce platforms must allocate fixed marketing budgets across multiple channels to maximize business utility. However, standard predict-then-optimiz

safetyarxiv-cs-lg

MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning

model-releasesarxiv-cs-ai

arXiv:2607.26465v1 Announce Type: new Abstract: Multimodal Large Language Models have sparked significant interest due to their potential for social intelligence; however, their ability to perform seq

Neural Network-Assisted CLEAN for Channel Modeling in Low-SNR Regimes

arXiv:2607.27450v1 Announce Type: new Abstract: Accurate multipath parameter estimation is critical for modern wireless communication systems, particularly in challenging low-SNR environments. Traditi

Hardware

ObjectStream: Latent Objects as Memory Anchors for Streaming Video Understanding

arXiv:2607.28312v1 Announce Type: new Abstract: Streaming video understanding requires models to continuously retain useful visual evidence before future questions are known. Existing approaches prima

hardwarearxiv-cs-cv

On-Policy and Off-Policy Learning for Large Action Spaces

arXiv:2607.28408v1 Announce Type: new Abstract: This thesis studies policy learning in interactive systems where an agent observes a context, selects an action from a very large set, and receives part

safetyarxiv-cs-lg

One Run Is Not an Idea: The Implementation Lottery in Automated Research

arXiv:2607.26587v1 Announce Type: cross Abstract: Automated research systems use experimental scores both to deliver artifacts and to decide which ideas to retain, transfer, and pursue. Yet one run sc

agentsarxiv-cs-ai