Search: “models”

Commonsense Reasoning in Computer Vision: Foundations, Recent Advancements, and Future Directions

arXiv:2609.05257v1 Announce Type: new Abstract: Commonsense reasoning in computer vision encompasses integrating visual data and contextual knowledge, crucial for enhancing AI's understanding of every

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Compact-Memory LLM Agents via Online Max-Member Clustering and Atom-Aware Packing

DGX agent

arXiv:2609.04915v1 Announce Type: new Abstract: Many long-horizon LLM deployments face tight prompt budgets: latency, cost, and context limits make full-context prompting impractical as interaction le

model-releasesarxiv-cs-ai

7 Sept 2026

Agents

Conformity Breaks Conformal Prediction

arXiv:2609.04445v1 Announce Type: cross Abstract: A conformal certificate can be valid when an LLM answers alone and invalid when the same LLM sees peers that unanimously assert a wrong answer. The qu

agentsarxiv-cs-cl

Constrained Sensing and Reliable State Estimation with Shallow Recurrent Decoders on a TRIGA Mark II Reactor

arXiv:2510.12368v2 Announce Type: replace-cross Abstract: Shallow Recurrent Decoder networks are a novel data-driven methodology able to provide accurate state estimation in engineering systems, such

researcharxiv-cs-lg

Corporate-Family Resolution Is Not a String-Matching Problem: A Public Benchmark Stratified by Name Visibility

arXiv:2609.04269v1 Announce Type: cross Abstract: Deciding whether two supplier records belong to the same corporate family is a prerequisite for spend consolidation, credit exposure aggregation and s

CoSkill: Joint Reinforcement Learning of Reasoning and Meta-Skill Agents for Hierarchical Skill Evolution

arXiv:2609.04865v1 Announce Type: new Abstract: Skill libraries improve the sample efficiency of agentic reinforcement learning (RL) by enabling large language model (LLM) agents to reuse procedural k

Disentangling Attention in Deep Operator Learning: A Controlled Study of Data-Driven and Physics-Informed Architectures

arXiv:2609.04407v1 Announce Type: new Abstract: Deep neural operators learn mappings between input functions and complete PDE solution fields, enabling forward evaluations of new problem instances ord

EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?

arXiv:2609.04280v1 Announce Type: cross Abstract: Modern LLM-based agents operate through a harness of tools, reusable skills, and specialist agents that shapes what they observe and what they can do.

From Deep to Shallow: Unconstrained and Efficient Layer Merging Strategy

arXiv:2609.04881v1 Announce Type: new Abstract: Although Deep Neural Networks have become foundational in many areas of Machine Learning, high computational demands limit their application in resource

From Plausible to Actionable: A Position on LLM Self-Explanations

arXiv:2607.15957v2 Announce Type: replace Abstract: Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as s

From Vision to Language: Investigating Causal Information Flow in Multimodal Decision-Making

arXiv:2609.05149v1 Announce Type: new Abstract: Vision-Language Models are commonly evaluated through their final predictions, but understanding whether these decisions are grounded in visual evidence

GNN-Guided Graph Coarsening and Adaptive QUBO Penalties for the Capacitated Vehicle Routing Problem with Time Windows on a Quantum Annealer

arXiv:2609.04593v1 Announce Type: new Abstract: Graph coarsening reduces the large Quadratic Unconstrained Binary Optimization (QUBO) formulations arising when vehicle-routing problems are solved by q

Hierarchical Possession-Aware Graph Pointer Network for Pass Receiver Selection

arXiv:2609.04803v1 Announce Type: new Abstract: Pass receiver selection is a fundamental task in football analytics, aiming to predict the intended receiver under a given game state. This task is chal

How a Chatbot's Response Style Shapes a Classroom: A Multi-Agent Simulation of Students Consulting AI

arXiv:2609.05018v1 Announce Type: cross Abstract: LLM-based chatbots are increasingly used as everyday confidants. Because they are designed to maximize user satisfaction, they can respond with excess

How Much Does Corpus Choice Change Dependency-Distance Estimates?

arXiv:2609.04223v1 Announce Type: new Abstract: Dependency-distance estimates derived from a single corpus are routinely treated as properties of a language, yet this assumption has not been tested ac

ICM-Bench: Person-Level Identity Reasoning in Multimodal Agents with Long-Term Memory

arXiv:2609.04438v1 Announce Type: new Abstract: Long-horizon multimodal agents should remember not only what happened but also who participated. This capability depends on linking recurring faces, voi

Influence Score and Transformers interpretability: Measure of the Effective Impact of Attention Heads at inference time

arXiv:2609.05074v1 Announce Type: new Abstract: We propose an influence score to quantify the contribution of attention heads to classification decisions in Transformer-based models designed for promp

Intrinsic Temporal Adaptation of CLIP for Partially Relevant Video Retrieval

arXiv:2609.04800v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos that contain moments relevant to a text query. Since the target moment occup

Latent-Aligned Reasoning for Multimodal Recommendation

arXiv:2609.04645v1 Announce Type: cross Abstract: Multimodal Vision-Language Models (VLMs) have demonstrated remarkable capabilities in cross-modal understanding, yet a fundamental challenge persists

safetyarxiv-cs-cl

Linguistic Trajectory Encoding for Efficient Long-Horizon Spatial Memory in Embodied Agents

arXiv:2609.04802v1 Announce Type: cross Abstract: Embodied agents performing long-horizon tasks require a memory representation in which the state transitions of dynamic objects remain queryable in na

LLM-Driven Algorithm Design for Quantum Circuit Synthesis based on Binary Decision Diagrams

arXiv:2609.05327v1 Announce Type: new Abstract: Quantum circuits are central to implementing quantum algorithms on quantum devices, where quantum gates must be reversible. Many quantum algorithms rely

Long Horizon Transformer Quantile Fault Prediction for Multi Site Industrial Predictive Maintenance

arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning wind

applicationsarxiv-cs-ai

Hardware

Low-Latency Spell Correction for Japanese Music Search Queries

arXiv:2609.04262v1 Announce Type: cross Abstract: Spell correction for Japanese search queries presents unique challenges due to the co-existence of four writing scripts (Latin/romaji, hiragana, katak

hardwarearxiv-cs-lg

Memory as transformation: LETHE, a self-referential gan-inspired architecture

arXiv:2609.04289v1 Announce Type: new Abstract: LETHE (Latent-parameter Evolution with Temporal Hierarchical quasi-Equilibrium) is a self-referential sonic-oblivion system implemented in SuperCollider

PAC-Bayesian Reconstruction Guarantees for Time Series Variational Autoencoders

arXiv:2609.05212v1 Announce Type: cross Abstract: Forecasting time series accurately is critical for applications with complex data ranging from energy systems to healthcare and finance. Among current

applicationsarxiv-cs-lg

Local Ai

PACE: Propagation-Aware Collaborative Correction for One-Shot Personalized Federated Graph Learning

arXiv:2609.04832v1 Announce Type: new Abstract: Client heterogeneity creates both an opportunity and a risk in personalized federated graph learning. Knowledge held by other subgraphs may complement a

local-aiarxiv-cs-lg

Partial Inverse Design of High-Performance Concrete Using Cooperative Neural Networks for Constraint-Aware Mix Generation

arXiv:2512.06813v3 Announce Type: replace-cross Abstract: High-performance concrete (HPC) requires complex mix design decisions involving interdependent variables and practical constraints. While data

Phase Transition Frequency as a Training Time Predictor of Test Accuracy in ResNets

arXiv:2609.05194v1 Announce Type: cross Abstract: The number of discrete class-separability jumps observed during ResNet finetuning is examined empirically as a predictor of final test accuracy. Acros

ProToMEx: Rapid, Interpretable Explanations via Structured Representations

arXiv:2609.04265v1 Announce Type: new Abstract: Existing post-hoc explainers for machine learning classifiers primarily focus on feature attribution, assigning importance scores to individual features

researcharxiv-cs-lg

ReaDiT Guidance: Control for Image and Video Generation using Diffusion Transformer Features

arXiv:2609.04649v1 Announce Type: new Abstract: We present DiT Readout (ReaDiT) Guidance, a lightweight framework for controlling generation with Diffusion Transformer (DiT) models via their internal

researcharxiv-cs-cv

Real-World Multi-Modal and Longitudinal Lung Cancer Dataset

arXiv:2609.05202v1 Announce Type: cross Abstract: Multi-modal learning has demonstrated strong potential in medical applications by integrating heterogeneous data sources such as medical imaging, clin

Reducing Hallucinated Transcripts in Whisper via Hallucination Space Projection

arXiv:2609.04561v1 Announce Type: new Abstract: Whisper is a widely used foundation model for automatic speech recognition (ASR), but its generative decoder can produce fluent hallucinated transcripts

Local Ai

RefDiT: Local Attribute Guidance in Reference-Based Image Generation

arXiv:2609.04976v1 Announce Type: new Abstract: Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global

local-aiarxiv-cs-cv

Risk-Aware Optimal Control with Rulebooks

model-releasesarxiv-cs-ro

arXiv:2609.05199v1 Announce Type: cross Abstract: We consider safety-critical control problems involving multiple requirements with different priorities and uncertainty in their evaluation. We represe

Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling

arXiv:2601.18049v2 Announce Type: replace Abstract: Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regarding feature extraction and classification perfo

Shadow Queries for Private Retrieval in Vector Databases

arXiv:2609.04767v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on information retrieval (IR) systems, such as Retrieval-Augmented Generation (RAG), to incorporate domai

Local Ai

Shared circuits predict whether LLMs generalize across formats in arithmetic reasoning

arXiv:2609.04463v1 Announce Type: cross Abstract: In many forms of reasoning, including arithmetic reasoning, generalizing across superficial changes in input format is effortless for humans: anyone w

local-aiarxiv-cs-ai

Solution-space heterogeneity shapes federated learning dynamics across partial differential equations

arXiv:2609.05012v1 Announce Type: new Abstract: Federated scientific machine learning enables institutions to train neural surrogates without centralizing local physical data, yet studies of partial d

Towards Efficient Evaluation of Evolutionary Transfer Optimization: Case Studies on Task-Parameterized Applications

arXiv:2609.05040v1 Announce Type: new Abstract: As evolutionary transfer optimization (ETO) scales to larger collections of related tasks, problem evaluation can become a major source of runtime growt

Train What You Deploy:Token-Faithful Post-Training of a Production Coding

arXiv:2609.04678v1 Announce Type: new Abstract: Existing post-training pipelines for coding and terminal agents suffer severe token and control fidelity errors: simplified training environments mismat

TRILOGUE: A Trilingual Spoken Dialogue Fact-Checking Benchmark with Evidence and Paired Audio

arXiv:2609.04452v1 Announce Type: new Abstract: Modern misinformation is often heard before it is read, yet fact-checking systems are still evaluated mainly on clean written claims. Spoken dialogue re

Vectorizing Classical Tamil: Representation Learning for Verse-Commentary Pairs

arXiv:2609.04755v1 Announce Type: new Abstract: We construct a corpus of 1,262 verse-commentary (urai) pairs from five Classical Tamil source sections, ranging from technical grammatical prose to mode

VICAL: Vicinal Consistency Alignment for Long-Tailed Visual Recognition

arXiv:2609.04948v1 Announce Type: cross Abstract: Multi-expert models have become the dominant paradigm for long-tailed learning, largely attributed to their presumed ability to benefit from expert di

What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Agents

arXiv:2609.04518v1 Announce Type: new Abstract: Agent reinforcement learning (RL) increasingly runs through full execution harnesses, and a multi-harness recipe mixes two choices: exposing the policy

A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications

arXiv:2412.06494v2 Announce Type: replace Abstract: Background. Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling collaborative AI in sensitive healthcar

A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions

arXiv:2609.04018v1 Announce Type: new Abstract: Quantile treatment effects (QTEs) measure the effect of a treatment on the distribution of an outcome, and their estimation at extreme quantile levels i

A Two-Stage Forecasting System for CPU Workload Prediction in Private Clouds

arXiv:2609.03457v1 Announce Type: new Abstract: Accurate cloud resource forecasting is essential for proactive resource provisioning, maintaining Quality of Service (QoS), and reducing operational cos

applicationsarxiv-cs-lg

AnyBox: Efficient Zero-Shot 9DoF Pose Estimation of Boxes for Robotic Manipulation

arXiv:2511.15884v2 Announce Type: replace-cross Abstract: Recovering the 9D pose of objects, both their 6D pose and 3D dimensions, under clutter and occlusion is a core requirement for warehouse autom

applicationsarxiv-cs-ai