Search: “models”

Domain-Aware Pruning: Sparsity and Domain Generalization via Regularized Probabilistic Masking

model-releasesarxiv-cs-lg

arXiv:2608.08624v1 Announce Type: new Abstract: Domain generalization (DG) and neural network pruning are conventionally treated as distinct objectives, targeting out-of-distribution (OOD) robustness

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Dynamic Distribution-Aware Uncertainty Tracking in Vision-Language Representation Learning

DGX agent

arXiv:2608.09011v1 Announce Type: new Abstract: Uncertainty Quantification (UQ) aims to measure the reliability of model predictions, serving as a critical safeguard for deploying Vision-Language Mode

safetyarxiv-cs-lg

11 Aug 2026

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding

arXiv:2506.19141v3 Announce Type: replace-cross Abstract: Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we intro

researcharxiv-cs-lg

Effect of Abstractions and Prompting Strategies on LLM-Guided High-Performance Optimizations

arXiv:2608.08085v1 Announce Type: cross Abstract: Code performance optimization is a vital aspect of modern software development, as it enables faster response times and reduced resource usage. These

Enhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings

arXiv:2508.17092v2 Announce Type: replace-cross Abstract: Knowledge Tracing (KT) aims to predict a student's future performance based on their sequence of interactions with learning content. Many KT m

Estimating Uncertainty in Galaxy Morphology Classification

arXiv:2608.08398v1 Announce Type: new Abstract: Astronomers classify galaxy morphology to investigate cosmic evolution. While deep foundation models are increasingly utilized in Galaxy Morphology Clas

Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agents

arXiv:2608.08793v1 Announce Type: new Abstract: Agent Skills package reusable instructions and assets for tool-using language-model agents. Progressive loading creates failure boundaries poorly repres

local-aiarxiv-cs-cl

FedA2L: Adaptive layer-wise learning rate adjustment in decentralized federated learning

arXiv:2608.09208v1 Announce Type: cross Abstract: Decentralized intelligence systems with heterogeneous devices and limited coordination increasingly rely on decentralized federated learning (DFL). Ho

FedTVD: Balancing Data Quality and Quantity for Robust Federated Learning

arXiv:2608.09221v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training across distributed client devices while preserving data privacy. However, FL faces signif

local-aiarxiv-cs-ai

From Benchmark Performance to Tool Deployment: Human-in-the-Loop Anomaly Detection

arXiv:2608.07770v1 Announce Type: cross Abstract: Automated anomaly detection methods often report strong performance on curated academic benchmarks, but their behavior under real-world industrial con

From Rebound to Remedy: Understanding and Mitigating Reward Hacking via Representation Engineering

arXiv:2604.01476v2 Announce Type: replace-cross Abstract: Reinforcement learning for LLMs is vulnerable to reward hacking, where models exploit shortcuts to maximize reward without solving the intende

safetyarxiv-cs-cl

Full-Feature versus Limited-Input Machine Learning for Residential Energy Estimation: A Comparative Analysis of RECS and ResStock Under Realistic Input Constraints

arXiv:2608.09255v1 Announce Type: new Abstract: Residential energy estimates are often needed before detailed envelope characteristics, equipment efficiencies, infiltration, sensor, or billing data ar

researcharxiv-cs-lg

Applications

How Simple Can It Get? From Interpretable Equations to Readable Rules for Financial Decision Making

arXiv:2608.09433v1 Announce Type: cross Abstract: In regulated domains such as finance, a model that cannot be explained cannot be deployed, yet many interpretable classifiers defeat their own purpose

applicationsarxiv-cs-ai

Instability of LLM Pre-Pretraining: It Doesn't Always Help. An Investigation on Multiple Languages

arXiv:2608.08800v1 Announce Type: new Abstract: Pretraining LLMs on artificial languages ('pre-pretraining') is a technique that could reportedly increase token efficiency by 33%, i.e., save up to 33%

InstructionCrafter: Generating Consistent and High-Fidelity Visual Instructions

arXiv:2608.08460v1 Announce Type: new Abstract: Given textual task instructions, generating step-by-step visual instructions as an image sequence requires the simultaneous satisfaction of multiple pro

Investigating Multimodal Informativity under Different Partner Visibility Conditions in Video-Mediated Dialogue

arXiv:2608.08915v1 Announce Type: new Abstract: Situated language use is multimodal and embodied. For example, gestures can carry information that is absent or underspecified in the speech signal, yet

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Is CLIP Cross-Eyed? Revealing and Mitigating Center Bias in the CLIP Family

arXiv:2604.05971v2 Announce Type: replace-cross Abstract: Recent research has shown that contrastive vision-language models such as CLIP often lack fine-grained understanding of visual content. While

safetyarxiv-cs-cl

JUMP-lite: Compact, reproducible benchmarking of cell representations

arXiv:2608.07632v1 Announce Type: cross Abstract: Image-based profiling captures rich phenotypic signatures for drug discovery and functional genomics. Large public datasets like JUMP Cell Painting no

Tutorials

Let Geometry GUIDE: Layer-wise Unrolling of Geometric Priors in Multimodal LLMs

arXiv:2604.05695v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in 2D visual tasks but still struggle to understand physical space in rea

tutorialsarxiv-cs-cv

LITEWAY: LIghtweight HAR via Temporal Efficient highWAY

arXiv:2608.09421v1 Announce Type: cross Abstract: Wearable human activity recognition (HAR) remains challenging due to the computational and energy constraints of deep learning models on resource-limi

LogiShot: Logically Coherent Cross-Shot Video Generation

arXiv:2608.08820v1 Announce Type: new Abstract: Generating cross-shot videos that are logically connected is essential for content creation. Currently, most cross-shot video-generation workflows, such

Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking

arXiv:2608.09613v1 Announce Type: new Abstract: Existing unified 4D reconstruction and point tracking approaches typically rely on heuristic interpolations or just predict at integer timestamps, lacki

MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architectures

arXiv:2608.07556v1 Announce Type: cross Abstract: Multi-agent systems (MAS) decompose long-horizon tasks across supervisors and subagents, but delegated goals do not necessarily carry their original a

Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory

model-releasesarxiv-cs-lg

arXiv:2509.10378v2 Announce Type: replace-cross Abstract: Linear systems arise in generating samples and in calculating observables in lattice quantum chromodynamics~(QCD). Solving the Hermitian posit

OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agents

arXiv:2608.08775v1 Announce Type: new Abstract: Agentic benchmarks aim to measure how well AI agents plan, search, execute, and recover within realistic multi-tool environments, but they are almost ex

OpenVisTool: An Open Recipe for Synthesizing Instructive Visual Tool-Use Trajectories

arXiv:2608.08557v1 Announce Type: new Abstract: Visual tool use has emerged as a fundamental capability for multimodal agents to actively acquire evidence beyond a fixed image encoding. The prevailing

Opportunity Is Not Realizability: Selection-Valid Diagnostics for Multi-LLM Routing

arXiv:2608.08265v1 Announce Type: new Abstract: Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best

researcharxiv-cs-lg

PosBridge: Multi-View Positional Embedding Transplant for Identity-Aware Image Editing

arXiv:2508.17302v2 Announce Type: replace Abstract: Localized subject-driven image editing aims to seamlessly integrate user-specified objects into target scenes. As generative models continue to scal

local-aiarxiv-cs-cv

Prompt Embedding Probes (PEP): Hallucination Detection in LLMs from Hidden States

arXiv:2608.08024v1 Announce Type: cross Abstract: Large language models (LLMs) can generate fluent and useful responses but remain prone to hallucinations. We introduce Prompt Embedding Probes (PEP),

PROSLEX: A Novel Dataset for Expert-Annotated Legal Statute Prediction for Indian Judiciary

arXiv:2608.08830v1 Announce Type: new Abstract: Legal Statute Prediction (LSP) involves automatically identifying relevant legal statutes given factual descriptions in legal documents, typically frame

Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis

arXiv:2509.21629v4 Announce Type: replace-cross Abstract: Program verification relies on loop invariants, yet automatically discovering strong invariants remains a long-standing challenge. We investig

RefineAny3D: Depth Refinement as Semantic Alignment for Monocular 3D Detection

arXiv:2608.09147v1 Announce Type: new Abstract: Monocular 3D object detection spans two regimes: closed-set detectors operating within a fixed category vocabulary, and open-vocabulary detectors that l

local-aiarxiv-cs-cv

REFRAMED: Towards Realistic Audio Description Generation for Movies

arXiv:2608.09765v1 Announce Type: new Abstract: Audio Description (AD) is a verbal narration of key visual content in videos, enabling access for visually impaired audiences. Unlike standard video cap

REIN: Bridging the Gap between Reasoning and Reliability via Reflection and Abstention Alignment

arXiv:2608.07931v1 Announce Type: new Abstract: Large reasoning models (LRMs) are prone to hallucination, which undermines their reliability and poses challenges for safe deployment. Hallucinations in

safetyarxiv-cs-ai

Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?

arXiv:2608.09629v1 Announce Type: new Abstract: Self-evolving agents are usually built around prescribed optimization pipelines: the framework decides how to gather evidence, revise a persistent artif

Revision or Re-Solving? Decomposing Second-Pass Gains in Multi-LLM Pipelines

arXiv:2604.01029v2 Announce Type: replace-cross Abstract: Multi-LLM revision pipelines, in which a second model reviews and improves a draft produced by a first, are widely assumed to derive their gai

RippleKV: Cross-Layer KV Cache Allocation via Perturbation Propagation

arXiv:2608.08684v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by KV cache memory, yet distributing a limited cache budget across layers remains challenging. Existing met

Applications

Search over the Visual World: Persistent Visual Memory, Layered Indexes, and Source-Grounded Evidence

arXiv:2608.08075v1 Announce Type: cross Abstract: Most video-retrieval systems assume a bounded corpus and return ranked files or timestamps. Agents operating over cameras, screens, streams, and archi

applicationsarxiv-cs-cv

Tabular Numeric Stretch Transformation

arXiv:2608.09162v1 Announce Type: cross Abstract: Tabular data presents unique challenges for deep learning due to its heterogeneous nature, where numeric features exhibit diverse distributions, scale

Tied Trit-Planes: Constraining PTQTP to a Uniform Nine-Level Quantizer, with a Persistent Folded Format for Disk-Streamed Mixture-of-Experts Serving

arXiv:2608.08910v1 Announce Type: new Abstract: PTQTP decomposes LLM weight matrices into two ternary (trit) planes with two free per-group scales. Tying the scales to a fixed ratio of three collapses

Towards Researcher Agents for Knowledge-Graph Question Answering

arXiv:2608.07700v1 Announce Type: new Abstract: Translating a natural-language question into a SPARQL query that can be executed against a large knowledge graph requires resolving lexical ambiguity, g

Trajectory Divergence Horizon Decision for Reliable Dual-Arm Surgical Subtask Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.09125v1 Announce Type: new Abstract: Surgical robotic systems are increasingly being adopted as clinical workload rises, motivating autonomous solutions for repetitive manipulation subtasks

Tutorials

UniDFKD: A Unified Semantic Prior Framework for Architecture-Agnostic Data-Free Knowledge Distillation

arXiv:2608.09287v1 Announce Type: cross Abstract: Data-Free Knowledge Distillation (DFKD) transfers knowledge from a pretrained teacher model to a compact student model by synthesizing semantically in

tutorialsarxiv-cs-ai

Tutorials

UniScale: Arbitrary-Scale Industrial Anomaly Generation

arXiv:2608.07864v1 Announce Type: new Abstract: Industrial anomaly inspection faces a major challenge due to the lack of real-world anomaly samples. While generative models are used to create anomaly

tutorialsarxiv-cs-cv

VIGIL: Tackling Hallucination Detection in Image Recontextualization

arXiv:2602.14633v2 Announce Type: replace Abstract: We introduce VIGIL (Visual Inconsistency & Generative In-context Lucidity), a benchmark dataset and framework that provides a fine-grained categoriz

When Do Task Vectors Interfere? Mapping the Validity Boundaries of Weight-Space Composition

model-releasesarxiv-cs-lg

arXiv:2608.09490v1 Announce Type: new Abstract: Task arithmetic treats fine-tuning displacements as composable directions in weight space, yet it remains unclear when parameter addition reflects predi

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No

arXiv:2608.08315v1 Announce Type: new Abstract: Multimodal LLMs that recognise events reliably still fail to say when they happen. Prompted for timestamps, strong VLMs reach as little as 3.8% R@0.5 on

Zero-shot 2D Grounding with Novel Affordance Types

arXiv:2608.08929v1 Announce Type: new Abstract: 2D affordance grounding aims to locate the region of an object that a human can interact with. Existing research focuses on recognizing affordance types