Search: “benchmark”

Let's Unlearn Stereotypes Before Decision-Making: Assessing the Impact of Intrinsic Bias Mitigation on Downstream Fairness in LLMs

arXiv:2509.16462v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used in high-stakes decision-making systems, where biased predictions can reinforce social and economi

safetyarxiv-cs-cl

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Research

LiFTER: A Grounded Neuro-Symbolic Microscope for Continuous-Time Dynamic Graph Forecasting

DGX agent

arXiv:2608.06765v1 Announce Type: new Abstract: Continuous-time dynamic graph models predict future links by compressing past interactions into neural states. Although effective for forecasting, this

researcharxiv-cs-ai

10 Aug 2026

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers

arXiv:2608.06867v1 Announce Type: new Abstract: No single large language model (LLM) is optimal across all queries and budget constraints, making model routing essential for cost-effective deployment.

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

LyEvO: Lyapunov-Guided Evolutionary Optimization for Safe and Robust Sim-to-Real Policy Learning

arXiv:2608.06481v1 Announce Type: cross Abstract: Training controllers that are safe and robust in simulation, and systematically assessing their readiness for real-world deployment, remain key challe

Measuring the Cross-Lingual Comprehension Gap: How the language of the evidence shapes what language models understand

arXiv:2608.06506v1 Announce Type: new Abstract: Language models are often evaluated as though capabilities demonstrated in English remain equally available when the same content is presented in other

researcharxiv-cs-cl

MemPrism: Task-Conditioned Relational Memory Views for Long-Horizon Agents

arXiv:2608.06745v1 Announce Type: new Abstract: Long-horizon agents rely on memory to reuse experiences, yet existing memory systems often assume that evidence can be directly consumed through a fixed

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence …

model-releasesyann-lecun--x

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta

Minimal Ingredients for Reward Assignment from Expert Demonstrations

arXiv:2506.06793v2 Announce Type: replace-cross Abstract: Reward assignment from scarce demonstrations is a key challenge in both offline and online imitation learning. A common and intuitive strategy

MirrorWorld: Taming Video Diffusion Models for Mirror Reflection Generation

arXiv:2608.07463v1 Announce Type: new Abstract: Recent advances in video diffusion models (VDMs) have enabled high-fidelity video synthesis. However, generating mirror reflections remains challenging

Modular TTT: Rethinking Test-Time Training as Composable Modules

arXiv:2608.07110v1 Announce Type: cross Abstract: Test-time training (TTT) views sequence modeling as an online learning problem in which fast weights are updated by an internal learning rule. Despite

Momba: Network Modernization Improves Multi-Objective Reinforcement Learning

arXiv:2608.07180v1 Announce Type: cross Abstract: Recent advances in deep reinforcement learning (RL) have shown that improving neural network architectures can yield substantial gains in sample effic

Multi Codec Discrete Diffusion Model for Text Guided Speech Inpainting and Editing

arXiv:2608.06424v1 Announce Type: cross Abstract: Speech recordings often contain missing, corrupted, or incorrect regions that must be reconstructed or modified without re-synthesizing the entire utt

Needle 2: 14MB agentic LLM for phones, wearables, smart home and robots.

model-releasesr-localllama

Hey LocalLlaMa, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots a

Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots

arXiv:2603.13108v2 Announce Type: replace-cross Abstract: Panoramic imagery provides holistic 360{eg} visual coverage for environmental perception in quadruped robots. However, existing occupancy pred

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings

arXiv:2511.23204v2 Announce Type: replace Abstract: Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exce

researcharxiv-cs-cv

People Are Not Just Their Countries. Disentangling Social Determinants of LLM Value Alignment Across Europe

arXiv:2608.07367v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of

Policy-Masked Private Experts: Auditable and Reversible Capability Access Control in Sparse MoE Models

model-releasesarxiv-cs-ai

arXiv:2608.06690v1 Announce Type: cross Abstract: Most language-model access controls regulate behavior while leaving the same computation available to every request. We study a different systems ques

Progressive Content Refinement with Decaying Reward Joint LinUCB

arXiv:2608.06750v1 Announce Type: cross Abstract: Iterative refinement has significantly enhanced Large Language Model (LLM) performance; however, existing methods ranging from feedback-based Self-Ref

PURe: A Plug-and-Play Product-Unit Residual Module for Vision Networks

model-releasesarxiv-cs-ai

arXiv:2505.04397v3 Announce Type: replace-cross Abstract: Modern vision networks are dominated by additive local transformations, whereas explicit multiplicative local interactions remain underexplore

QFCQT: A Chaotically Gated Quantformer Framework for Volatile Time-Series Forecasting

arXiv:2608.07363v1 Announce Type: new Abstract: Forecasting non-stationary time series remains difficult due to long-range dependencies, local volatility bursts, structural shifts, and nonlinear oscil

Quantization Damage Is Multiplicative, Not Additive

arXiv:2608.06564v1 Announce Type: cross Abstract: Quantization is how large language models are actually deployed, and below four bits it is known to hurt. What nobody can say is which of the model's

Applications

Real-time Whole-Body Motion Planning for Mobile Manipulators Carrying Arbitrarily Shaped Payloads via Kinematically-Coupled SVSDF

arXiv:2608.07005v1 Announce Type: new Abstract: Mobile manipulators are increasingly tasked with transporting large, non-convex payloads through cluttered environments, yet existing planners either ov

applicationsarxiv-cs-ro

Representation-driven Endoscopic Visual Embedding Alignment for Latent Generation

arXiv:2608.07176v1 Announce Type: cross Abstract: Developing foundation generative models for endoscopy is limited by the gap between natural and clinical images and the computational cost of training

Retrieval-Constrained Policy Optimization for Attack Technique Extraction from Cyber Threat Intelligence

arXiv:2608.06778v1 Announce Type: cross Abstract: Mapping cyber threat intelligence (CTI) text to MITRE ATT&CK techniques is essential for structured threat analysis, yet manual annotation is costly a

Retrofitting Linear Attention into Diffusion Language Models

model-releasesarxiv-cs-lg

arXiv:2608.06628v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer a promising alternative to autoregressive models by accelerating inference through parallel decoding. Recent dLL

Same Attention, Different Truths: Put Logit-Lens over Visual Attention to Detect and Mitigate LVLM Object Hallucination

arXiv:2608.07302v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) often suffer from object hallucination, generating objects that are absent from the image. Prior work largely att

Agents

SkillAligner: Treating Retrieved Skills as Adaptable Drafts at Execution Time

arXiv:2608.06880v1 Announce Type: new Abstract: General-purpose skills promise reusable procedural knowledge for language agents, yet semantic relevance does not guarantee execution utility: a retriev

agentsarxiv-cs-lg

Agents

SkillProx: Self-Evolving Agent Skills via Proximal Textual Gradient Descent

arXiv:2608.07449v1 Announce Type: new Abstract: LLM agents increasingly adapt to recurring tasks by accumulating procedural knowledge in skills. These skills are lightweight, reusable textual artifact

agentsarxiv-cs-ai

SLED: Scalable Location Encoding via Distillation

model-releasesarxiv-cs-ai

arXiv:2608.06612v1 Announce Type: cross Abstract: The plethora of readily available geospatial data offers exciting opportunities to learn high quality representations of the planet, but the sheer siz

SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection

arXiv:2603.21638v2 Announce Type: replace Abstract: Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into

Spatiotemporal Agility: Time-Constrained Reinforcement Learning for Vision-Guided Dynamic Quadrupedal Interception

model-releasesarxiv-cs-ro

arXiv:2608.06907v1 Announce Type: new Abstract: Legged robots require robust agility to perceive and interact with complex and dynamic environments within a constrained time. However, most existing qu

Stoicheia: Character-Level Masked Diffusion for Ancient Greek Textual Restoration, Parsing, and Metrical Scansion

arXiv:2608.07249v1 Announce Type: new Abstract: We introduce Stoicheia, a 405M-parameter character-level masked-diffusion encoder for Ancient Greek whose input factors into five aligned, independently

Sub-Quadratic Bisimulation Metrics via Approximate Nearest Neighbors: Coverage-Augmented Guarantees and Computable Two-Sided Certificates

model-releasesarxiv-cs-lg

arXiv:2608.06762v1 Announce Type: new Abstract: Bisimulation metrics quantify behavioral similarity in Markov decision processes, but their Wasserstein fixed-point operator updates every state pair an

Symbolic Graphics Programming with Large Language Models

arXiv:2509.05208v2 Announce Type: replace Abstract: Large language models (LLMs) excel at program synthesis, yet their ability to produce symbolic graphics programs (SGPs) that render into precise vis

Tutorials

Target-Weighted Neyman Allocation: Experimental Design for Heterogeneous Treatment Effects under Population Shift

arXiv:2608.06512v1 Announce Type: new Abstract: Randomized experiments are often run in one population to guide decisions in another. Allocating by experimental proportions wastes budget on groups tha

tutorialsarxiv-cs-lg

TEMPO: Semantic-Action Decoupled RL Post-Training for Vision-Language-Action Models

arXiv:2608.07314v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are commonly adapted to downstream manipulation tasks via supervised fine-tuning (SFT) or online reinforcement lea

Tensor Network Kernel Machines: A JAX Framework for Machine Learning and Nonlinear System Identification

model-releasesarxiv-cs-lg

arXiv:2608.07043v1 Announce Type: cross Abstract: Developing nonlinear models that are both expressive and computationally efficient remains a challenge in machine learning and nonlinear system identi

TEXAS: Task-Expert-Aware Supervision for Downstream Mixture-of-Experts LLM Adaptation

arXiv:2608.06396v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models route each token through a small subset of experts, making routing patterns useful for identifying task-relev

The successor to Llama is here, and Meta is revitalizing focus on open weights with their new Muse Glimmer - a leading 30B param model desig…

The successor to Llama is here, and Meta is revitalizing focus on open weights with their new Muse Glimmer - a leading 30B param model designed for always-on local agent use, small enough to run on a

model-releasesollama--x

Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection

arXiv:2608.07015v1 Announce Type: new Abstract: Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains an

researcharxiv-cs-cv

Tutorials

UniJEPA: A Unified Joint-Embedding Predictive Architecture for Task-Agnostic Visual World Modeling

arXiv:2608.07409v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) have emerged as a principled framework for self-supervised learning of world models in compact latent s

tutorialsarxiv-cs-cv

Unmasking Removal-Budget Confounding: A Matched Operating-Point Evaluation Framework for Adaptive Data Cleaning

arXiv:2608.06511v1 Announce Type: new Abstract: Adaptive data-cleaning methods replace manual filtering thresholds with data-driven partitions. However, changing the partition granularity, the number

safetyarxiv-cs-lg

Unsupervised Adaptation of PDE Foundation Models

arXiv:2608.07053v1 Announce Type: new Abstract: Pretrained partial differential equation (PDE) foundation models can generalize across different equations, but adapting them to unseen PDE systems typi

Applications

When GNNs Fail: Quantifying and Overcoming Temporal Correlation Volatility in Time Series

arXiv:2608.07333v1 Announce Type: new Abstract: Modeling multivariate time series by representing them as graphs, where individual series act as nodes and pairwise temporal corre- lations serve as edg

applicationsarxiv-cs-lg

24 GB of VRAM is not really 24 GB for a local LLM. Here is the worksheet I use

I kept seeing model file size compared directly with the number printed on the GPU box. That misses several memory buckets. A simple planning model is: usable capacity = advertised VRAM x 0.90 total t

model-releasesr-ollama

9 Aug 2026

Building a budget 32GB → 48GB VRAM home AI server: 2-3x RX 9060 XT 16GB vs RTX 5060 Ti 16GB, AM5 vs used EPYC?

model-releasesr-localllama

I’m planning a dedicated home AI server, mainly for local LLM inference, agents/tool use, Docker services, and eventually larger MoE models with CPU offload. My plan is to start with 2x 16GB GPUs = 32

8 Aug 2026

I tested a fresh GitHub download → Ollama → first local coding-agent task (72 seconds, no cloud API)