Search: “benchmark”

DeMMO: Longitudinal and Cross-Disease Modelling of Digital Mobility Outcomes via Multi-Task Learning

arXiv:2608.25073v1 Announce Type: new Abstract: Digital mobility outcomes (DMOs) derived from wearable sensors characterise mobility in daily life and offer a promising means of monitoring disease pro

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From smart wheelchairs to the ML Reproducibility Checklist, Joelle's research has affected improvements in machine learning around the world…

DGX agent

From smart wheelchairs to the ML Reproducibility Checklist, Joelle's research has affected improvements in machine learning around the world. Today, she’s helping build secure, sovereign AI systems th

model-releasescohere--x

27 Aug 2026

Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality

arXiv:2608.25807v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) replace fixed activations in deep architectures with learnable univariate edge functions, making the choice of edge pa

If you maintain a skill library for long-horizon agents, this one is worth your time. (bookmark it) It discusses one of most common topics I…

If you maintain a skill library for long-horizon agents, this one is worth your time. (bookmark it) It discusses one of most common topics I get asked about these days. It shares some good ideas on ho

model-releasesdair-ai--x

InsightSR: Refining Symbolic Regression Search Spaces via Parallel Semantic and Structural LLM Guidance

arXiv:2608.25291v1 Announce Type: new Abstract: Symbolic regression (SR) seeks to discover parsimonious mathematical laws from observational data, yet conventional approaches often struggle with the v

Learning New Facts with QLoRA: An Acquisition-Retention Frontier

model-releasesarxiv-cs-cl

arXiv:2608.25677v1 Announce Type: new Abstract: Parameter-efficient fine-tuning is often assumed to preserve pretrained capabilities because it updates only a small number of parameters. We show that

Research

LongVU-TTT: Causal Test-Time Training for Visual Resampling in Long Video Understanding

arXiv:2608.25729v1 Announce Type: new Abstract: Long-video MLLMs must model temporal change before a limited visual-token budget removes most frame evidence. We introduce LongVU-TTT, which inserts a c

researcharxiv-cs-cv

MAMA-FLUX.2: Image-to-Image Synthesis of Post-Contrast Breast DCE-MRI for the MAMA-SYNTH Challenge

arXiv:2608.25648v1 Announce Type: new Abstract: Dynamic contrast-enhanced breast MRI is central to cancer diagnosis and monitoring, but requires gadolinium-based contrast agents. In this work, we addr

MIMONet: Multi-scale Input and Multi-scale Output Network for Salient Object Detection

arXiv:2608.25733v1 Announce Type: new Abstract: The existing methods for saliency detection task focus on the application of multi-level features, aiming to take advantage of the respective strengths

Agents

MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation

arXiv:2608.25085v1 Announce Type: new Abstract: Clinical diagnosis is fundamentally interactive and incremental, yet the dominant paradigm for evaluating Large Language Models (LLMs) in medicine remai

agentsarxiv-cs-cl

My first week on ollama

I work on SEO, copywriting, research, etc I’ve used openrouter before but I’ve spent way more for the same amount of work. Deepseek V4 is still the king for me, didn’t found better orchestrator for my

model-releasesr-ollama

Neat paper suggesting that human augmentation and task automation are not necessarily related. Models that are really good at doing work are…

model-releasesethan-mollick--x

Neat paper suggesting that human augmentation and task automation are not necessarily related. Models that are really good at doing work are not always good at helping humans do work better. Given the

Research

One way to think of current AI is as a big sponge for patterns. It absorbs and operationalizes any pattern it is exposed to (albeit with ver…

researchfrancois-chollet--x

One way to think of current AI is as a big sponge for patterns. It absorbs and operationalizes any pattern it is exposed to (albeit with very low data efficiency at training time). Once you can progra

ONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures

model-releasesarxiv-cs-cl

arXiv:2510.04938v2 Announce Type: replace-cross Abstract: Neural architecture search (NAS) automates the design process of high-performing architectures, but remains bottlenecked by expensive performa

Query-Side Attacks on GNN-Based KGQA: Tracing Failures from Entity Linking to Answer Generation

model-releasesarxiv-cs-cl

arXiv:2608.25922v1 Announce Type: new Abstract: GNN-based Knowledge Graph Question Answering (KGQA) pipelines process queries through four discrete stages: entity linking, subgraph retrieval, GNN reas

SNAP-KG: Streaming Node Assignment via Projection for Knowledge Graph Entity Integration

arXiv:2608.25149v1 Announce Type: new Abstract: Knowledge graph (KG) construction pipelines must continuously integrate newly arriving entities into a growing graph. Unlike inserting triples between e

Agents

We've introduced native, agentic spreadsheet extraction 📊 into LlamaParse. Spreadsheets are a wildly different format from PDFs (or any oth…

We've introduced native, agentic spreadsheet extraction 📊 into LlamaParse. Spreadsheets are a wildly different format from PDFs (or any other document format). They can span arbitrarily many rows/colu

agentsjerry-liu--x

Research

When Pruning Meets Interpretability: Preserving Sparse Autoencoder Robustness in LLMs

arXiv:2608.25941v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are widely used to interpret the internal representations of large language models (LLMs), yet their reliability under post-h

researcharxiv-cs-lg

When Should a Network Emit Geometry, and When Should It Detect It? Readout, Reconciliation, and Representation in Floorplan Vectorization

arXiv:2608.25608v1 Announce Type: new Abstract: A network trained to recover the walls, openings, and rooms of a rasterized floorplan can produce its output in two ways: by emitting the geometry as an

A 27b model beating latest frontier models was not on my 2026 bingo card

model-releasesr-localllama

https://preview.redd.it/kbsqh6f7molh1.png?width=730&format=png&auto=webp&s=068dbea9a50be634a369d54d8b27b781d020fab3 My experience with Qwen 3.8 for agentic tasks has been phenomenal but I personally f

A tale of perfect fit and phantom optima: how data-driven models can fail in real-time optimization

arXiv:2608.23885v1 Announce Type: cross Abstract: Real-time optimization (RTO) relies on process models to locate economically optimal operating conditions. Because developing first-principles models

Safety

Adaptive Multi-Mode Out-of-Distribution Detection for Trajectory Prediction in Autonomous Vehicles

arXiv:2509.13577v3 Announce Type: replace Abstract: Trustworthy trajectory prediction grounds autonomous vehicle (AV) safety, yet deployed models inevitably face out-of-distribution (OOD) scenes. Prio

safetyarxiv-cs-cv

ADVERSA: Measuring Multi-Turn Guardrail Degradation and Judge Reliability in Large Language Models

arXiv:2603.10068v2 Announce Type: replace-cross Abstract: Most adversarial evaluations of large language model (LLM) safety assess single prompts and report binary pass/fail outcomes, which fails to c

Amortized Set Prediction for Inverse IFS Reconstruction from Density Maps

arXiv:2608.24175v1 Announce Type: new Abstract: Iterated Function Systems (IFS) generate self-similar fractals from a few contractive affine maps. The forward map from parameters to images is computat

Agents

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

arXiv:2608.23858v1 Announce Type: cross Abstract: The Agent Payments Protocol (AP2), introduced by Google, enables large language model (LLM)-driven shopping agents to authorize and execute payments o

agentsarxiv-cs-ai

CAFE: Self-Improving Search Agents Need Co-Evolving Feedback

arXiv:2608.24794v1 Announce Type: new Abstract: Outcome-supervised search agents learn when and how to retrieve evidence, but terminal rewards neither localize intermediate errors nor redirect an ongo

Local Ai

CRISP: Calibration-Aware Visual State Space Duality for Remote Sensing Semantic Segmentation

arXiv:2608.23746v1 Announce Type: new Abstract: State space models, especially Visual State Space Duality (VSSD), have emerged as efficient linear-time alternatives to Transformers for dense visual ta

local-aiarxiv-cs-cv

crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023

arXiv:2506.12006v4 Announce Type: replace-cross Abstract: The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medic

Safety

Do Robotic World Models Really Follow Actions? Diagnosing and Aligning Action-Conditioned Generation for Policy Learning

arXiv:2608.24885v1 Announce Type: cross Abstract: Action-conditioned world models are increasingly used as learned simulators for policy evaluation and improvement, yet their effectiveness rests on an

safetyarxiv-cs-cv

From Causal Plausibility to Causal Reliability: Evaluating LLMs as Calibrated Direct Causal-Edge Classifiers

arXiv:2608.23660v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to provide prior causal knowledge for structural causal discovery, yet whether their direct-edge ju

HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA

arXiv:2402.01767v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) significantly improves document-based question answering by integrating external documents during generat

HMGCLIP: Heterogeneous Multi-Granularity Contrastive Learning for E-commerce Representation Learning

arXiv:2608.24467v1 Announce Type: new Abstract: Although recent Multimodal Large Language Models (MLLMs) have advanced general product understanding, they implicitly encode product information into gl

How I see the future for local AI

model-releasesr-localllama

I think that mall models between 10B and 40B are the real gamechanger. These models will be the ones that will make the AI buble pop and big companies like Anthropic and OpenAi go to hell. We are curr

MARS: Multi-Specialist LLM Relay System for Competitive Programming

arXiv:2608.23918v1 Announce Type: new Abstract: Large Language Models excel at code generation, yet competitive programming exposes a persistent failure mode: existing multi-agent pipelines distribute

Mind the Student: Behavioral and Contextual Cues for Automated Engagement Prediction in Online Learning

arXiv:2608.24340v1 Announce Type: cross Abstract: The prediction of student engagement from the online tutoring videos is difficult because engagement is a multidimensional construct comprising distin

Open Source Kernel in Qwen3.6-35B-A3B for AMD MI350X: 78,498 output tok/s on 8 GPUs

model-releasesr-localllama

So here's the thing, almost everyone use NVIDIA to run their LLMs, we also do the same, a lot of people we've met use like RTX PRO 6000 or even H100, B300 It seems like everyone eyes is looking at NVI

Safety

PhysMLLMs: Spatial Priors for Unified Referring Segmentation and Grounded Reasoning of Images and Videos

arXiv:2608.24574v1 Announce Type: new Abstract: Video multimodal large language models support language guided video segmentation, but they often show spatio temporal inconsistencies, e.g., jitter, dr

safetyarxiv-cs-ai

PuzzleKV: Page-Wise Low-Rank Decomposition for KV Cache Compression

arXiv:2608.23843v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is increasingly limited by the memory required for the key-value (KV) cache. KV cache compression

Recursive Experiential-Working Memory Evolution for Long-Horizon Agent Harnesses

arXiv:2608.24876v1 Announce Type: new Abstract: Recursive self-improvement (RSI) remains hard in long-horizon tasks, where growing histories obscure the task state and misalign skill invocation. We in

Relative Time Intervals Representation for Word-level Timestamping with Masked Training

arXiv:2608.24041v1 Announce Type: new Abstract: Although Speech Large Language Models (SpeechLLMs) excel at speech understanding and generation, their capacity for fine-grained, temporally aligned out

ReproAgent: Contract-Guided Paper-to-Code Reproduction

arXiv:2608.24291v1 Announce Type: new Abstract: Paper-to-code reproduction asks scientific AI agents to turn research papers into executable repositories that preserve the paper's method, protocol and

SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction

arXiv:2608.24252v1 Announce Type: new Abstract: LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic dr

Scalable and Versatile Identification for Hierarchical Structural Causal Models: A New Look at Project STAR

arXiv:2608.24500v1 Announce Type: cross Abstract: The STAR (Student-Teacher Achievement Ratio) experiment (1985, Tennessee, USA) is a landmark hierarchical dataset designed to assess the impact of cla

Segmentation-Guided Homography Estimation for Long-Term Planar Tracking

arXiv:2602.19624v2 Announce Type: replace Abstract: Recent state-of-the-art visual trackers produce high quality and long-term-stable segmentation masks. We propose to leverage these strengths for pla

SonarLLM: A Native Sonar--Optical Multimodal Large Language Model for Underwater Perception

arXiv:2608.24325v1 Announce Type: new Abstract: Reliable underwater perception requires complementary sensing under variable visibility. Optical cameras capture appearance and semantics but degrade ra

StateTune: Transforming LLM-Assisted EDA Flow Tuning into a Stateful, Closed-Loop Process

arXiv:2608.23601v1 Announce Type: cross Abstract: EDA flow parameter tuning is critical for quality-of-results~(QoR), yet the parameter space is large, tightly coupled, and full evaluations are prohib

StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing

arXiv:2608.24777v1 Announce Type: new Abstract: LLM-based agents can interact with external environments through tool invocation, but this capability also introduces security risks such as file modifi

Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core

arXiv:2608.24810v1 Announce Type: new Abstract: Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing approaches still rely on buffering clips or windo