Search: “framework”

CASE: Cadence-Aware Set Encoding for Large-Scale Next Basket Repurchase Recommendation

model-releasesarxiv-cs-lg

arXiv:2604.06718v2 Announce Type: cross Abstract: Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a

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Research

Clickbait detection: quick inference with maximum impact

DGX agent

arXiv:2604.08148v1 Announce Type: new Abstract: We propose a lightweight hybrid approach to clickbait detection that combines OpenAI semantic embeddings with six compact heuristic features capturing s

researcharxiv-cs-cl

10 Apr 2026

Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection

arXiv:2506.19420v2 Announce Type: replace Abstract: Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many dow

Applications

CompoDistill: Attention Distillation for Compositional Reasoning in Multimodal LLMs

arXiv:2510.12184v2 Announce Type: replace Abstract: Recently, efficient Multimodal Large Language Models (MLLMs) have gained significant attention as a solution to their high computational complexity,

applicationsarxiv-cs-cv

Contextualising (Im)plausible Events Triggers Figurative Language

arXiv:2604.07885v1 Announce Type: new Abstract: This work explores the connection between (non-)literalness and plausibility at the example of subject-verb-object events in English. We design a system

Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models

arXiv:2604.08527v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models under their own induced distribution while leveraging supervision from stronger teachers. We identify

DietDelta: A Vision-Language Approach for Dietary Assessment via Before-and-After Images

arXiv:2604.06352v1 Announce Type: cross Abstract: Accurate dietary assessment is critical for precision nutrition, yet most image-based methods rely on a single pre-consumption image and provide only

researcharxiv-cs-ai

Tutorials

Diffusion Processes on Implicit Manifolds

arXiv:2604.07213v1 Announce Type: new Abstract: High-dimensional data are often modeled as lying near a low-dimensional manifold. We study how to construct diffusion processes on this data manifold in

tutorialsarxiv-cs-lg

Agents

DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather

arXiv:2604.08074v1 Announce Type: new Abstract: Reliable and weather-robust perception systems are essential for safe autonomous driving and typically employ multi-modal sensor configurations to achie

agentsarxiv-cs-cv

Direct Segmentation without Logits Optimization for Training-Free Open-Vocabulary Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.07723v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment arbitrary category regions in images using open-vocabulary prompts, necessitating that exis

Tutorials

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

arXiv:2402.02249v3 Announce Type: replace Abstract: We study how to best spend a budget of noisy labels to compare the accuracy of two binary classifiers. It's common practice to collect and aggregate

tutorialsarxiv-cs-lg

DP-DeGauss: Dynamic Probabilistic Gaussian Decomposition for Egocentric 4D Scene Reconstruction

arXiv:2604.07986v1 Announce Type: new Abstract: Egocentric video is crucial for next-generation 4D scene reconstruction, with applications in AR/VR and embodied AI. However, reconstructing dynamic fir

DYCP: Dynamic Context Pruning for Long-Form Dialogue with LLMs

arXiv:2601.07994v4 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly operate over long-form dialogues with frequent topic shifts. While recent LLMs support extended context wi

researcharxiv-cs-cl

Hardware

DynLP: Parallel Dynamic Batch Update for Label Propagation in Semi-Supervised Learning

arXiv:2604.06596v1 Announce Type: cross Abstract: Semi-supervised learning aims to infer class labels using only a small fraction of labeled data. In graph-based semi-supervised learning, this is typi

hardwarearxiv-cs-lg

E-3DPSM: A State Machine for Event-Based Egocentric 3D Human Pose Estimation

arXiv:2604.08543v1 Announce Type: new Abstract: Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolut

ECLipsE-Gen-Local: Efficient Compositional Local Lipschitz Estimates for Deep Neural Networks

arXiv:2510.05261v2 Announce Type: replace Abstract: The Lipschitz constant is a key measure for certifying the robustness of neural networks to input perturbations. However, computing the exact consta

researcharxiv-cs-lg

Efficient Learned Data Compression via Dual-Stream Feature Decoupling

arXiv:2604.07239v1 Announce Type: cross Abstract: While Learned Data Compression (LDC) has achieved superior compression ratios, balancing precise probability modeling with system efficiency remains c

researcharxiv-cs-lg

Efficient Provably Secure Linguistic Steganography via Range Coding

arXiv:2604.08052v1 Announce Type: new Abstract: Linguistic steganography involves embedding secret messages within seemingly innocuous texts to enable covert communication. Provable security, which is

researcharxiv-cs-cl

Local Ai

EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration

arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri

local-aiarxiv-cs-ai

Fail2Drive: Benchmarking Closed-Loop Driving Generalization

model-releasesarxiv-cs-cv

arXiv:2604.08535v1 Announce Type: cross Abstract: Generalization under distribution shift remains a central bottleneck for closed-loop autonomous driving. Although simulators like CARLA enable safe an

Tutorials

Few-Shot Incremental 3D Object Detection in Dynamic Indoor Environments

arXiv:2604.07997v1 Announce Type: new Abstract: Incremental 3D object perception is a critical step toward embodied intelligence in dynamic indoor environments. However, existing incremental 3D detect

tutorialsarxiv-cs-cv

Flux Attention: Context-Aware Hybrid Attention for Efficient LLMs Inference

model-releasesarxiv-cs-cl

arXiv:2604.07394v1 Announce Type: cross Abstract: The quadratic computational complexity of standard attention mechanisms presents a severe scalability bottleneck for LLMs in long-context scenarios. W

Force-Aware Residual DAgger via Trajectory Editing for Precision Insertion with Impedance Control

arXiv:2603.04038v2 Announce Type: replace Abstract: Imitation learning (IL) has shown strong potential for contact-rich precision insertion tasks. However, its practical deployment is often hindered b

safetyarxiv-cs-ro

Agents

Formally Guaranteed Control Adaptation for ODD-Resilient Autonomous Systems

arXiv:2604.07414v1 Announce Type: cross Abstract: Ensuring reliable performance in situations outside the Operational Design Domain (ODD) remains a primary challenge in devising resilient autonomous s

agentsarxiv-cs-ro

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning

arXiv:2604.06262v1 Announce Type: cross Abstract: Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-con

researcharxiv-cs-ai

From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations

model-releasesarxiv-cs-cl

arXiv:2507.05179v4 Announce Type: replace Abstract: In an era of rampant misinformation, generating reliable news explanations is vital, especially for under-represented languages like Hindi. Lacking

Hardware

Full State-Space Visualisation of the 8-Puzzle: Feasibility, Design, and Educational Use

arXiv:2604.06186v1 Announce Type: cross Abstract: Search algorithms are a foundational topic in artificial intelligence education, yet even simple domains can generate large state spaces that challeng

hardwarearxiv-cs-ai

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting

arXiv:2604.07928v1 Announce Type: new Abstract: While AI-based numerical weather prediction (NWP) enables rapid forecasting, generating high-resolution outputs remains computationally demanding due to

Local Ai

Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria

arXiv:2604.06018v2 Announce Type: replace-cross Abstract: This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study. The

local-aiarxiv-cs-ai

Governed Capability Evolution for Embodied Agents: Safe Upgrade, Compatibility Checking, and Runtime Rollback for Embodied Capability Modules

arXiv:2604.08059v1 Announce Type: new Abstract: Embodied agents are increasingly expected to improve over time by updating their executable capabilities rather than rewriting the agent itself. Prior w

safetyarxiv-cs-ro

Hardware

Graph Neural ODE Digital Twins for Control-Oriented Reactor Thermal-Hydraulic Forecasting Under Partial Observability

arXiv:2604.07292v1 Announce Type: new Abstract: Real-time supervisory control of advanced reactors requires accurate forecasting of plant-wide thermal-hydraulic states, including locations where physi

hardwarearxiv-cs-lg

Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations

arXiv:2604.07517v1 Announce Type: new Abstract: Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vas

safetyarxiv-cs-ro

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis

arXiv:2604.08301v1 Announce Type: new Abstract: The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently,

haha cool, this worked. an MCP server that allows Claude to build it's own reusable skills https://github.com/yoheinakajima/selfMCP (1473 Lo…

model-releasesyohei-nakajima--x

haha cool, this worked. an MCP server that allows Claude to build it's own reusable skills https://github.com/yoheinakajima/selfMCP (1473 LoC) basically a server with skills to CRUD skills in this vid

Local Ai

Hallucination Detection and Evaluation of Large Language Model

arXiv:2512.22416v2 Announce Type: replace Abstract: Hallucinations in Large Language Models (LLMs) pose a significant challenge, generating misleading or unverifiable content that undermines trust and

local-aiarxiv-cs-cl

HingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues

arXiv:2604.06845v1 Announce Type: cross Abstract: Long-term memory is critical for dialogue systems that support continuous, sustainable, and personalized interactions. However, existing methods rely

How SAP Concur automates expense reporting with agentic AI

model-releasesgoogle-cloud-ai

For decades, expense automation relied on a simple premise: If the machine can read the text, it can do the work. But anyone who has ever tried to scan a crumpled, smudged, or sun-bleached receipt fro

HST-HGN: Heterogeneous Spatial-Temporal Hypergraph Networks with Bidirectional State Space Models for Global Fatigue Assessment

arXiv:2604.08435v1 Announce Type: new Abstract: It remains challenging to assess driver fatigue from untrimmed videos under constrained computational budgets, due to the difficulty of modeling long-ra

Agents

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing s…

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing so much in deepagents) we always wanted to run llms in a loop

agentsharrison-chase--x

Information as Structural Alignment: A Dynamical Theory of Continual Learning

arXiv:2604.07108v1 Announce Type: cross Abstract: Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existi

Inside-Out: Measuring Generalization in Vision Transformers Through Inner Workings

arXiv:2604.08192v1 Announce Type: cross Abstract: Reliable generalization metrics are fundamental to the evaluation of machine learning models. Especially in high-stakes applications where labeled tar

safetyarxiv-cs-cv

Knowledge Graphs Generation from Cultural Heritage Texts: Combining LLMs and Ontological Engineering for Scholarly Debates

arXiv:2511.10354v1 Announce Type: cross Abstract: Cultural Heritage texts contain rich knowledge that is difficult to query systematically due to the challenges of converting unstructured discourse in

Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains

arXiv:2602.13235v2 Announce Type: replace-cross Abstract: Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a gi

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning

arXiv:2604.07941v1 Announce Type: new Abstract: Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervise

Applications

Large Language Models for Outpatient Referral: Problem Definition, Benchmarking and Challenges

arXiv:2503.08292v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly applied to outpatient referral tasks across healthcare systems. However, there is a lack of stan

applicationsarxiv-cs-ai

Learning to Negotiate: Multi-Agent Deliberation for Collective Value Alignment in LLMs

arXiv:2603.10476v2 Announce Type: replace Abstract: LLM alignment has progressed in single-agent settings through paradigms such as RL with human feedback (RLHF), while recent work explores scalable a

Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers

arXiv:2604.07822v1 Announce Type: new Abstract: We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models

researcharxiv-cs-cl

Low-Rank Key Value Attention

arXiv:2601.11471v3 Announce Type: replace Abstract: The key-value (KV) cache is a primary memory bottleneck in Transformers. We propose Low-Rank Key-Value (LRKV) attention, which reduces KV cache memo

researcharxiv-cs-lg