Search: “papers”

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection

model-releasesarxiv-cs-ai

arXiv:2508.20766v2 Announce Type: replace-cross Abstract: Safety alignment in Large Language Models (LLMs) often involves mediating internal representations to refuse harmful requests. Recent research

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Uncertainty-Aware Multimodal Anti-UAV Detection via Evidential Fusion and Conflict-Discounted Belief Aggregation

DGX agent

arXiv:2608.29235v1 Announce Type: new Abstract: Anti-UAV perception systems must remain reliable when sensor streams degrade under occlusion, fast motion, or modality-specific failure. Existing multim

model-releasesarxiv-cs-cv

1 Sept 2026

Uncertainty-Aware Trajectory Forecasting from Imperfect Tracking

arXiv:2608.30899v1 Announce Type: new Abstract: Most trajectory forecasting models are trained on clean annotated histories, and are often evaluated under the same idealized assumption, although pract

applicationsarxiv-cs-cv

Validating FKG.in: Soundness Assessment in LLM-Augmented Indian Food Knowledge

arXiv:2608.29249v1 Announce Type: new Abstract: The online culinary ecosystem is increasingly populated by recipe content generated, modified, or summarized by Large Language Models (LLMs). While ofte

researcharxiv-cs-ai

Local Ai

Vehicle Drift Emergence: Continuous Evolution from Grip Driving to the Handling Limit via Boundary Exploration Learning Model Predictive Control

arXiv:2608.28723v1 Announce Type: new Abstract: Automated drift controllers commonly track a prescribed drift equilibrium, sideslip reference, or trajectory. These formulations establish how to execut

local-aiarxiv-cs-ro

Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning

arXiv:2505.16567v4 Announce Type: replace-cross Abstract: Finetuning open-weight Large Language Models (LLMs) is standard practice for achieving task-specific performance improvements. Until now, fine

researcharxiv-cs-ai

What It Costs to Compose, Rebuild, and Correct Precomputed Memory

arXiv:2608.30647v1 Announce Type: new Abstract: Language models can answer from precomputed memory, a model's saved reading of a body of material, reused across requests instead of read again at each.

When History Is Multimodal: Rethinking Context Management for Long-Horizon Agents

arXiv:2608.29897v1 Announce Type: new Abstract: Long-horizon agents need a context manager to compress growing interaction histories into a bounded working context, via passive strategies or active st

safetyarxiv-cs-cl

X-Coder: Advancing Competitive Programming with Synthetic Tasks, Solutions, and Tests

arXiv:2601.06953v3 Announce Type: replace Abstract: Competitive programming remains challenging for code LLMs. Despite recent progress, many training pipelines still depend on scarce real-world data,

A Probabilistic Interpretation of KV Cache Eviction

arXiv:2608.28293v1 Announce Type: new Abstract: The premise and promise of KV (cache) eviction is simple: higher throughput can be achieved by evicting some entries from the KV cache, at a negligible

researcharxiv-cs-cl

Ada-TokenCom: Rate-Adaptive Token Communications via Large-Model-Driven Token Compression and Generation

arXiv:2608.28086v1 Announce Type: cross Abstract: Token Communications (TokenCom) has recently emerged as a new paradigm in which tokens serve as unified units for communication and computation, enabl

Amortizing intractable inference in diffusion models for vision, language, and control

arXiv:2405.20971v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as effective distribution estimators in vision, language, and reinforcement learning, but their use as priors in

Attribute Token Arithmetic: Disentangled and Continuous Semantic Control for Visual Autoregressive Models

arXiv:2608.28082v1 Announce Type: new Abstract: Autoregressive text-to-image generation has recently achieved remarkable progress, offering high-fidelity synthesis via a unified generative framework.

Local Ai

Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning

arXiv:2608.27715v1 Announce Type: new Abstract: Federated learning systems are increasingly deployed to facilitate collaborative model training across a heterogeneous client population. Existing pract

local-aiarxiv-cs-lg

Beyond the Rabbit Hole: Mapping the Relational Harms of QAnon Radicalization

arXiv:2601.17658v2 Announce Type: replace Abstract: Large-scale computational research on conspiracy theories has focused exclusively on believers' online behavior, leaving the harm experienced by tho

researcharxiv-cs-cl

Biases in Expected Goals Models Confound Finishing Ability

arXiv:2401.09940v2 Announce Type: replace Abstract: Expected Goals (xG) has emerged as a popular tool for evaluating finishing skill in soccer analytics. It involves comparing a player's cumulative xG

safetyarxiv-cs-lg

Biologically Inspired Mechanisms for Facilitating Grokking in Multilayer Perceptrons

arXiv:2608.28184v1 Announce Type: new Abstract: Grokking is a delayed transition from memorization to generalization that is often accompanied by substantial reorganization of internal representations

researcharxiv-cs-lg

ChainSplat: A Physics-Inspired Screw-Theoretic Model for Learning Deformable Linear Object Dynamics from Multi-View RGB Videos

arXiv:2608.28570v1 Announce Type: new Abstract: Identifying the underlying dynamics and 3D geometry of deformable linear objects (DLOs), such as cables, ropes, and hoses, is essential for accurate rob

applicationsarxiv-cs-ro

CoCoBench: A Cooperative Coordination Benchmark for Embodied Multi-Agent Task Planning

model-releasesarxiv-cs-ro

arXiv:2608.28266v1 Announce Type: new Abstract: Agent systems powered by multimodal large language models (MLLMs) have advanced rapidly in recent years, yet existing embodied-agent benchmarks still la

Agents

Cooperative Risk-Aware Exploration in Heterogeneous Multi-Robot Systems Using Algorithmic Altruism

arXiv:2608.28409v1 Announce Type: new Abstract: Multi-robot systems are well-positioned for exploration in hazardous environments, but effective deployment requires deciding not only where robots shou

agentsarxiv-cs-ro

Coordinated Motion Planning for Multi-Arm Systems via Iterative LQ Games

arXiv:2608.27726v1 Announce Type: new Abstract: Multi-agent motion planning for high-degree-of-freedom robotics manipulators in shared workspaces remains a fundamental yet challenging problem. Central

safetyarxiv-cs-ro

D-TAIA: Domain-Aware LLM Adaptation for Multi-Task Predictive Process Monitoring

model-releasesarxiv-cs-lg

arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c

Depth-Aware Pothole Detection Using YOLO and RT-DETR at the Edge

arXiv:2608.27633v1 Announce Type: new Abstract: Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly cont

safetyarxiv-cs-cv

Diffusion models as plug-and-play priors

arXiv:2206.09012v4 Announce Type: replace-cross Abstract: We consider the problem of inferring high-dimensional data mathbf{x} in a model that consists of a prior p(mathbf{x}) and an auxiliary differe

Agents

Distributed Model-Based Diffusion: Finite Horizon Contraction under Bounded Delay

arXiv:2608.27685v1 Announce Type: new Abstract: Simultaneously optimizing the trajectories of multiple agents is a challenging problem plagued by nonlinearity, nonconvexity, and the curse of dimension

agentsarxiv-cs-ro

Embedding Models for Stance-Aware Argument Retrieval

arXiv:2608.28283v1 Announce Type: new Abstract: In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks

safetyarxiv-cs-cl

Entity-Memory Graph Retrieval Improves Evidence Coverage in Long-Conversation Question Answering

arXiv:2608.27925v1 Announce Type: new Abstract: Entity-Memory graph retrieval keeps dialogue turns as verbatim Memory nodes, links repeated mentions through shared Entities, and connects adjacent Memo

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

arXiv:2305.12474v4 Announce Type: replace Abstract: Large Language Models(LLMs) have demonstrated remarkable performance across various natural language processing tasks; however, how to comprehensive

Ex-Sim(3)-Reg: 2D-3D Correspondence Pruning via Extended Sim(3) Registration

model-releasesarxiv-cs-cv

arXiv:2608.28096v1 Announce Type: new Abstract: Learning-based image-to-point-cloud (I2P) registration has garnered increasing attention in recent years. Nevertheless, existing methods still struggle

FENCE: A Financial and Multimodal Jailbreak Detection Dataset

arXiv:2602.18154v3 Announce Type: replace Abstract: Jailbreaking poses a significant risk to the deployment of Large Language Models (LLMs) and Vision Language Models (VLMs). VLMs are particularly vul

safetyarxiv-cs-cl

Tutorials

Generalized Context in Cross Attention for Transfer Learning of Disjoint Tabular Data

arXiv:2608.28209v1 Announce Type: new Abstract: Unlike images and text, applying transfer learning to tabular data is challenging due to heterogeneity in feature types, structures, and semantics acros

tutorialsarxiv-cs-lg

GLM 5.3 and GLM 5.3 Flash ran locally on RTX PRO 6000 WS and built a penthouse using BlenderMCP

model-releasesr-localllama

I keep seeing demos of AI agents building scenes in Blender through BlenderMCP, so I tried it myself. I ran both models locally for this and picked the GLM 5.3 family(Q4 quant) because videos of it do

Agents

Hierarchical Feature-level Reverse Propagation for Post-Training Neural Networks

arXiv:2506.07188v2 Announce Type: replace Abstract: End-to-end neural networks have become a dominant paradigm in autonomous driving, where reliable deployment requires controllable post-training adap

agentsarxiv-cs-cv

Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

arXiv:2305.19366v3 Announce Type: replace Abstract: Generative Flow Networks (GFlowNets), a class of generative models over discrete and structured sample spaces, have been previously applied to the p

safetyarxiv-cs-lg

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

arXiv:2305.17010v4 Announce Type: replace Abstract: Combinatorial optimization (CO) problems are often NP-hard and thus out of reach for exact algorithms, making them a tempting domain to apply machin

researcharxiv-cs-lg

Linear Temporal Logic Translation via Human-Inspired Self-Constrained Reasoning for Robot Task Specification

arXiv:2608.28435v1 Announce Type: new Abstract: Many robotic tasks are temporally extended and demand precise specifications of subgoals, constraints, and their temporal ordering. Yet human operators

researcharxiv-cs-ro

Lossy Event Compression: From Event Stream Distortion to Task Performance

arXiv:2608.28429v1 Announce Type: new Abstract: Event cameras generate asynchronous, sparse data streams with microsecond temporal resolution, but in moderate-to-high motion scenes they can produce as

[new @activegraphai blog post] How Synthetic Players used ActiveGraph to verify 4,919 runs without new model calls https://activegraph.ai/bl…

model-releasesyohei-nakajima--x

[new @activegraphai blog post] How Synthetic Players used ActiveGraph to verify 4,919 runs without new model calls https://activegraph.ai/blog/synthetic-players-activegraph-replay For the increasing n

Non-Uniform Quantisation for 3DGS Compression

model-releasesarxiv-cs-cv

arXiv:2608.28272v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, yet its high bitrate requirements pose significant challenges

Tutorials

Object Reconstruction under Occlusion with Generative Priors and Contact-induced Constraints

arXiv:2512.05079v2 Announce Type: replace Abstract: Object geometry is key information for robot manipulation. Yet, object reconstruction is a challenging task because camera observations are partial

tutorialsarxiv-cs-cv

Local Ai

Optimal 1.25 bit quantization of Qwen3.8-Flash-Next

Hello! I was looking into quantizing models and i saw how Hy4 was shrunk from 1.5 TB to 200GB with high retention in benchmarks (98% i think). I was wondering if: a) it would be worth it to attempt th

local-air-localllama

Optimal Transport for Network Comparison: A Review with Machine Learning Applications

arXiv:2608.27500v1 Announce Type: cross Abstract: Network comparison using optimal transport is a growing area of research in network science. Unlike standard graph metrics, optimal transport computes

applicationsarxiv-cs-lg

PhyMamba: Physics-Modulated Mamba for Robust Battery Health Prognostics

arXiv:2608.27978v1 Announce Type: new Abstract: Battery health prognostics is a core function in battery management systems (BMSs), yet long-horizon health forecasting from BMS signals remains challen

researcharxiv-cs-lg

Probabilistic Multi-Robot Gas Source Localization with Uncalibrated Sensors: A Distributed Estimation Approach

model-releasesarxiv-cs-ro

arXiv:2608.28214v1 Announce Type: new Abstract: Estimating environmental states with multi-robot systems becomes particularly challenging when robots are equipped with uncalibrated and therefore heter

Select, Don't Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection

arXiv:2608.27470v1 Announce Type: new Abstract: Entity Disambiguation (ED) is a key task for constructing and using knowledge graphs. State-of-the-art neural approaches commonly model ED as a single t

Self-Explainable Multi-Label Graph Neural Network for Correlated Evidence Attribution

arXiv:2608.27574v1 Announce Type: new Abstract: Multi-label graph learning intends to capture the intrinsic complexity of real-world applications, where one sample is often related to multiple groups

applicationsarxiv-cs-lg

SymboLLM-FE: LLM-Accelerated Symbolic Regression for Automated Feature Engineering on Tabular Data

arXiv:2608.28408v1 Announce Type: new Abstract: Tabular data, as a core data format in machine learning, often lacks the discriminative power needed for high-performance modeling due to insufficient f

safetyarxiv-cs-lg

Tutorials

Texture Image Classification Using DWT AlexNet Feature Fusion and Deep Neural Networks

arXiv:2608.28524v1 Announce Type: new Abstract: Texture image classification plays a significant role in computer vision applications, including industrial inspection, medical image analysis, remote s

tutorialsarxiv-cs-cv