Search: “benchmark”

ROMNet: a hybrid reduced order modeling and machine learning approach to waveform inversion

arXiv:2608.25160v1 Announce Type: cross Abstract: Waveform inversion seeks to estimate the wave speed of a heterogeneous, inaccessible medium, from time-resolved measurements of the waves at user cont

researcharxiv-cs-lg

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Agents

Routed Graph Handoff: Adaptive Format Selection for Multi-Agent LLM Delegation

DGX agent

arXiv:2608.25277v1 Announce Type: new Abstract: Multi-agent LLM systems coordinate through natural-language messages that consume 40--60% of their token budget. Replacing these with structured graphs

agentsarxiv-cs-cl

27 Aug 2026

RSFusionDet: Underwater RGB-Sonar Multimodal Object Detection

arXiv:2608.25367v1 Announce Type: new Abstract: Underwater unimodal object detection faces many challenges in sensor imaging, such as optical images limited by underwater noise and visible distance, a

Segmentation-Based Attention Entropy: Detecting and Mitigating Object Hallucinations in Large Vision-Language Models

arXiv:2603.16558v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) achieve strong performance on many multimodal tasks, but object hallucinations severely undermine their reliabi

researcharxiv-cs-cv

SelfGraphRAG: Bridging the Supervision Gap in Graph-Based RAG with Synthetic QA Generation

arXiv:2608.25123v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language models by incorporating external knowledge without retraining, but existing methods often u

researcharxiv-cs-cl

Semi-Supervised Adaptation of Vision-Language Models for Image Classification

arXiv:2608.25485v1 Announce Type: new Abstract: Vision-language models like CLIP have shown sig- nificant potential in handling natural images, yet their perfor- mance is often limited by the distinct

SHIFT-LLM: Distribution Shift Correction in Depth-Pruned LLMs

arXiv:2608.25068v1 Announce Type: new Abstract: Depth pruning removes entire Transformer blocks to reduce the inference cost of large language models, but disrupts the hidden-state distributions expec

SHSP: Structure-Aware Hierarchical Solution Prediction for Mixed-Integer Linear Programming

arXiv:2608.25282v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental optimization paradigm in combinatorial optimization and has been widely applied across real-wor

applicationsarxiv-cs-lg

Simultaneous inference of environmental and interaction forces in collective dynamics

arXiv:2608.25181v1 Announce Type: new Abstract: Collective dynamics arise in a wide range of physical, biological, and engineering applications. Examples include cell migration, swarm robotics, social

Skill Issue: Are Skills Language-Invariant in LLMs?

model-releasesarxiv-cs-cl

arXiv:2608.25832v1 Announce Type: new Abstract: Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with diff

SkyDrive: Learning to Drive in a New City from Aerial Traffic Monitoring

model-releasesarxiv-cs-ro

arXiv:2608.25142v1 Announce Type: new Abstract: Autonomous driving has made remarkable progress through imitation learning with massive human demonstration data. However, a trained planner often degra

SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spotting

arXiv:2608.25493v1 Announce Type: new Abstract: Continuous sign language recognition (CSLR) aims to recognize gloss sequences from unsegmented sign videos under weak sequence-level supervision. Howeve

StablePDENet: Enhancing Neural Operator Stability through Physics-Informed Residual-Sensitivity Regularization

arXiv:2601.06472v2 Announce Type: replace Abstract: Learning solution operators for differential equations with neural networks has shown great potential in scientific computing, but ensuring their st

TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

arXiv:2608.25935v1 Announce Type: new Abstract: Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To addre

agentsarxiv-cs-cv

Theoretically Principled Federated Learning for Balancing Privacy and Utility

arXiv:2305.15148v3 Announce Type: replace Abstract: We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the t

Three-Way Open-Set Detection for Robust Autonomous Navigation

arXiv:2511.15343v2 Announce Type: replace Abstract: Autonomous navigation in complex scenes requires reliable perception across scenarios that the model did not encounter during its training. Along it

agentsarxiv-cs-cv

Towards A Unified Information Bottleneck Framework for Time Series Explanations

arXiv:2608.25897v1 Announce Type: new Abstract: Explaining deep learning models operating on time series data is crucial in various applications that require transparent and interpretable insights int

applicationsarxiv-cs-lg

TraceML: An Empirical Analysis of Human-Agent Planning in Machine Learning Development

arXiv:2608.26086v1 Announce Type: new Abstract: Large language models write correct code for isolated problems but remain far weaker at autonomous machine-learning development, where an agent must rev

agentsarxiv-cs-lg

Training-Free Interaction-Aligned Visual Token Pruning for Efficient Embodied Manipulation

arXiv:2603.22991v2 Announce Type: replace Abstract: Efficient visual representation is a central image-processing challenge in embodied manipulation, where policies repeatedly process dense visual-tok

Trust the Mass: Forced Weights in KV-Cache Eviction

model-releasesarxiv-cs-cl

arXiv:2608.25230v1 Announce Type: cross Abstract: Every deployed sparse-attention or KV-cache-eviction rule keeps a subset of the keys, discards the rest, and renormalizes the attention weights over t

Tutorials

TTSR: Test-Time Self-Evolving via Reflection

arXiv:2603.03297v2 Announce Type: replace Abstract: Test-time training (TTT) adapts large language models (LLMs) during inference using only unlabeled test inputs. Existing methods, however, face two

tutorialsarxiv-cs-cl

V-Rubrics: Visual Faithfulness via Rubric-Based Reinforcement Learning

arXiv:2608.25580v1 Announce Type: new Abstract: Vision-language models can produce fluent answers that are insufficiently grounded in the visual evidence: a single unsupported object, chart value, or

VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning

arXiv:2608.26105v1 Announce Type: new Abstract: Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be u

VISA: Agentic Self-Evolving Data Synthesis for Multimodal Instruction Following

arXiv:2608.26013v1 Announce Type: new Abstract: Multimodal instruction-following models require training data that is accurate, diverse, verifiable, and challenging. Existing synthesis pipelines typic

agentsarxiv-cs-cl

Visual General Intelligence: A White Paper

arXiv:2608.25924v1 Announce Type: new Abstract: This paper reconsiders intelligence from a vision-centered perspective and examines whether intelligence emerging from visual experience and learning ma

researcharxiv-cs-cv

WAVE: Reversing the Guidance Hierarchy for Coarse-to-Fine Guided Depth Super-Resolution

arXiv:2608.25302v1 Announce Type: new Abstract: Guided depth super-resolution (GDSR) typically extracts RGB guidance features through convolutional hierarchies, inheriting their fine-to-coarse bias. T

We’re the Team Behind Apodex 1.1 — Ask Us Anything!

model-releasesr-localllama

Hi r/LocalLLaMA ! We’re Apodex, the team behind Apodex 1.1, our new model family built to scale agentic intelligence for complex work. We’re excited to be here and answer your questions directly. Apod

What Should a Large Language Model See? Physical Invariants as a Data Representation for PDE Discovery

arXiv:2608.25189v1 Announce Type: new Abstract: Understanding how molecular interactions govern macroscopic behaviour is a central challenge in molecular sciences. However, conventional theory buildin

Where to Look Matters: On-Policy Self-Distillation for Long-Video Understanding

arXiv:2608.25356v1 Announce Type: new Abstract: Vision-language models (VLMs) have made substantial progress in long-video understanding, with standard backbone models typically answering questions fr

Why and When Neural Networks Improve Local Approximation in Optimization

arXiv:2608.24963v1 Announce Type: new Abstract: Published experience with neural surrogates in derivative-free optimisation is contradictory: the same family of models that cuts the evaluation count o

A Heterogeneous Mixture of Experts Framework for Interpretable Machine Learning

arXiv:2608.24195v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models provide a flexible framework for partitioning complex prediction problems into simpler local learning tasks through an

A Human-Factors Guided Cognitive Model of Visuospatial Complexity in Embodied Active Vision

model-releasesarxiv-cs-ai

arXiv:2608.23572v1 Announce Type: cross Abstract: We propose a novel framework for the analysis of multimodal data -- encompassing visual, auditory, and spatial stimuli -- foregrounding the role of co

A Hybrid Two-Stage Machine Learning Pipeline for Fault Detection and Classification in Power Transmission Systems

arXiv:2608.23726v1 Announce Type: cross Abstract: Rapid and accurate fault detection in high-voltage transmission networks is essential for grid reliability and equipment protection. Transmission faul

A mesh-free multiresolution deep energy method with phase-field modeling of brittle fracture

arXiv:2608.24126v1 Announce Type: new Abstract: Phase-field modeling of brittle fracture removes the need to track cracks explicitly by recasting their evolution as the minimization of an energy funct

A Multimodal Foundation Model for Longitudinal Patient Representation and Scalable Insight Generation in Oncology

arXiv:2608.24688v1 Announce Type: new Abstract: Precision oncology necessitates a longitudinal model of patient state that captures cancer evolution and treatment over time, integrating multimodal obs

applicationsarxiv-cs-lg

Absorbing Gradient Conflicts: Modeling Semantic Variance via Kent Distributions for Cross-Modal Hashing

arXiv:2608.24010v1 Announce Type: new Abstract: Supervised proxy-based deep cross-modal hashing has become the dominant paradigm for large-scale retrieval. However, prevalent methods model class proxi

Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems

model-releasesarxiv-cs-ai

arXiv:2608.24361v1 Announce Type: new Abstract: Multi-agent LLM systems are increasingly deployed in real-world applications, where failures can be costly and difficult to localize. Despite growing ef

Alibaba releases Qwen3.8-Flash, an open-weight, 125B-parameter model built on its next-gen Qwen 4 architecture, saying it rivals Opus 4.6 and V4-Flash (Luz Ding/Bloomberg)

Luz Ding / Bloomberg: Alibaba releases Qwen3.8-Flash, an open-weight, 125B-parameter model built on its next-gen Qwen 4 architecture, saying it rivals Opus 4.6 and V4-Flash — Alibaba Group Holding Ltd

model-releasestechmeme

Analytical Covariance Propagation for DVL-Aided Loosely Coupled SINS Under Attitude Uncertainty

arXiv:2601.19509v2 Announce Type: replace Abstract: In loosely coupled strapdown inertial navigation system/Doppler velocity log (SINS/DVL) integration, the body-frame DVL velocity is projected into t

researcharxiv-cs-ro

Anatomy of a Scam Call: What 10,000 real scam and spam calls reveal about how phone scammers operate

arXiv:2608.24127v1 Announce Type: cross Abstract: Telephone fraud is pervasive and costly, but its inner workings are rarely observed at scale. We analyze a complete corpus of 10,211 inbound scam and

At a 1M-token context length, QSA’s attention kernel is up to 7.6× faster in prefill and 4.9× faster in decode. With a 90% prefix-cache hit …

At a 1M-token context length, QSA’s attention kernel is up to 7.6× faster in prefill and 4.9× faster in decode. With a 90% prefix-cache hit rate, Qwen3.8-Flash-Next delivers 8.6× the prefill throughpu

model-releasesqwen--x

Local Ai

AURASeg: Attention-Guided Upsampling with Residual-Assisted Boundary Refinement for Drivable-Area Segmentation

arXiv:2510.21536v5 Announce Type: replace-cross Abstract: Free-space segmentation is essential for autonomous robots to identify drivable regions and navigate safely across indoor, outdoor, and road-s

local-aiarxiv-cs-cv

Beyond Accuracy: A Dual-Judge Evaluation Protocol for Vision-Language Models in Legally Grounded Tasks

arXiv:2608.24258v1 Announce Type: new Abstract: AI systems are increasingly evaluated for legally accountable settings, where correct outputs must also be justifiable against an applicable legal stand

applicationsarxiv-cs-ai

Beyond Confidence: Test-Time Scaling for Multi-Turn Search Agents via Retrieval Grounding

arXiv:2608.24024v1 Announce Type: new Abstract: Confidence-based voting aggregates parallel LLM rollouts by weighting each with internal signals such as token log probabilities, and has been actively

agentsarxiv-cs-ai

Beyond OAuth: Task-Scoped Authorization for AI Agents via Natural Language Slices

model-releasesarxiv-cs-ai

arXiv:2603.17170v2 Announce Type: replace-cross Abstract: AI agents increasingly execute users' natural-language (NL) tasks by calling Web services, yet today's Web authorizes these calls through OAut

Brain makes a user’s full history available to Computer without loading all of it into every prompt. Agents can explore it on demand, verify…

Brain makes a user’s full history available to Computer without loading all of it into every prompt. Agents can explore it on demand, verify claims against the underlying evidence, and keep it current

agentsperplexity--x

Bridging Adversarial and Collaborative Learning for AI-Generated Image Quality Assessment

arXiv:2608.24372v1 Announce Type: new Abstract: AI-generated image quality assessment (AIGIQA) requires jointly reasoning about perceptual fidelity and prompt alignment, two quality dimensions that ar

Claude is an incredible coding agent. I use it a lot. (Also Codex and start checking Cursor again). But I’m not convinced the AI-native SDLC…

model-releasesitamar-friedman--x

Claude is an incredible coding agent. I use it a lot. (Also Codex and start checking Cursor again). But I’m not convinced the AI-native SDLC is the existing SDLC with a magical Claude wand waved over