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SSMB: Self-Supervised Local Feature Detection under Motion Blur

arXiv:2608.27181v1 Announce Type: new Abstract: Keypoint detection under motion blur remains a significant challenge, as blur distorts local image structure and degrades the repeatability of feature l

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Stable but Wrong: When Learning Stabilizes Away from the Truth

DGX agent

arXiv:2603.21491v2 Announce Type: replace Abstract: Stable training is often treated as evidence that learning is succeeding, but stability characterizes optimization behavior rather than correctness

safetyarxiv-cs-lg

28 Aug 2026

Stack Trace-Based Crash Deduplication with Transformer Adaptation

arXiv:2508.19449v2 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer wo

STAR : Sentence Translation Alignment Rate for Document-to-Document Machine Translation

arXiv:2608.27161v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled a shift from sentence-level to document-to-document (Doc2Doc) machine translation, promising improved global c

STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation

arXiv:2505.20781v2 Announce Type: replace-cross Abstract: Off-policy evaluation (OPE) estimates the performance of a target policy using offline data collected from a behavior policy, and is crucial i

Style as a Confound: False Positives in AI Detection of Non-Native Academic Writing

arXiv:2608.26710v1 Announce Type: new Abstract: AI text detectors are increasingly employed in academic settings, but it remains unclear whether their outputs reflect AI authorship itself or broader l

Subspace Alignment for Vision-Language Model Test-time Adaptation

arXiv:2601.08139v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation

Surgical Video Generation From Diffusion to World Models: A Survey

arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio

TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack

arXiv:2608.26126v1 Announce Type: new Abstract: Telecommunications is a high-leverage domain for large language model (LLM)-based reasoning because routine engineering workflows require joint groundin

The Artificial Experimentalist: Discovery and Control of Self-Organizing Phenomena with Autotelic Reinforcement Learning

arXiv:2608.26116v1 Announce Type: new Abstract: Existing methods for exploring cellular automata and other complex systems mostly operate in open loop: they set initial conditions, execute a full simu

The Latent Diagnostic Taxonomy: A Framework for Constructing Classifiers and Diagnosing Their Decisions, Applied to Prompt Injection Detection

arXiv:2608.26423v1 Announce Type: cross Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for developing a complementary diagnostic that identifies whic

🚨 There are now 23 lawsuits related to deaths or self-harm from ChatGPT. ChatGPT bombarded Rita Chesterton with 1,600 messages in just 9 da…

🚨 There are now 23 lawsuits related to deaths or self-harm from ChatGPT. ChatGPT bombarded Rita Chesterton with 1,600 messages in just 9 days calling her delusions “sacred, hard work,” and told her sh

safetygary-marcus--x

Toward Equitable Low-Carbon Mobility: Fairness-Aware Demand Prediction for Expanding Bike-Sharing Systems

arXiv:2608.26451v1 Announce Type: new Abstract: Bike-sharing systems are an important component of low-carbon urban mobility, but continued expansion creates challenges in both cold-start prediction a

Training-Time Explainability for Multilingual Hate Speech Detection: Aligning Model Reasoning with Human Rationales

arXiv:2608.26125v1 Announce Type: cross Abstract: Online hate against Muslim communities often appears in culturally coded, multilingual forms that evade conventional AI moderation. Such systems, thou

TransMeme: A Multi-Agent Framework for Cross-Cultural Meme Transcreation

arXiv:2608.27127v1 Announce Type: new Abstract: Internet memes are a pervasive form of multimodal online communication; however, such communication often involves users from diverse linguistic and cul

TrapVLA: Trapping Vision-Language-Action Models in Configured Failure Modes

arXiv:2608.26578v1 Announce Type: cross Abstract: This work introduces Configured Failure Trapping, a novel backdoor attack task against Vision-Language-Action (VLA) models, which aims to activate att

TTPO: Test-Time Policy Optimization

arXiv:2608.27448v1 Announce Type: new Abstract: Recent prominent post-training methods, such as Reinforcement Learning (RL) and On-Policy Self-Distillation (OPSD), have driven rapid progress in mathem

Unsupervised Adaptation of 3D CT Foundation Models for 3D CBCT Segmentation

arXiv:2608.27190v1 Announce Type: new Abstract: Accurate 3D segmentation of cone-beam CT (CBCT) is critical for interventional and radiation therapy applications, yet it remains limited by two compoun

VFA: Empowering Multilingual MLLMs via Vision-Free Adaptation

arXiv:2608.26155v1 Announce Type: cross Abstract: Multimodal large language models have advanced rapidly, yet most remain English-centric, as scaling multilingual multimodal instruction tuning is limi

Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

arXiv:2608.27065v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has recently emerged as an effective post-training paradigm that improves policy optimization through dense token-lev

WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression

arXiv:2608.26239v1 Announce Type: new Abstract: Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, plannin

safetyarxiv-cs-ro

When Memory Takes Gradients: Collaborative Vector Memory for Agentic Recommender Systems

arXiv:2608.26895v1 Announce Type: cross Abstract: Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memor

4DGS-WAM: Bridging Past and Future with an Object-Centric World Action Model based on 4D Gaussian Splatting

arXiv:2608.25956v1 Announce Type: new Abstract: Current world action models (WAMs) typically operate on 2D visual data. These models can achieve exceptional visual quality, but they lack explicit spat

A Token-Level Analysis of Sampled-Token Reverse-KL On-Policy Distillation

arXiv:2608.25643v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises a student on its own trajectories with token-level signals from a frozen teacher, yet how a sampled loss alloc

A Visual Dependence-Aware Framework for Multimodal Unsupervised Continual Post-Training

arXiv:2608.26095v1 Announce Type: new Abstract: In this paper, we explore a novel task of Multimodal Unsupervised Continual Post-Training (MU-CPT), enabling deployed MLLMs to continually evolve from s

Activation Steering Transfer to Agents: One Gain Ratio Does Not Identify Potency and Efficacy

arXiv:2607.09156v2 Announce Type: replace Abstract: Additive activation steering is calibrated in single-turn chat and then deployed inside agent scaffolds. The quantity usually reported for that move

Adaptive Triggering for Bias Correction in LLM Reasoning

arXiv:2608.25379v1 Announce Type: new Abstract: Chain-of-thought prompting can expose and amplify demographic stereotypes within an LLM's intermediate reasoning and create a failure mode that final-an

AdaptiveEmbed: Sample-Adaptive Multi-Vector Representation for Multimodal Retrieval

arXiv:2608.25412v1 Announce Type: new Abstract: Multi-vector representations have emerged as an effective paradigm for multimodal retrieval, representing each sample with multiple complementary embedd

Advantage-Driven Explicit Memory for Social Navigation

arXiv:2608.25610v1 Announce Type: new Abstract: Robot policies are predominantly learned with classical parametric variants of imitation learning or RL, where training stores the agent's behavior excl

safetyarxiv-cs-ro

Anchoring Bias in LLM-as-a-Judge Systems: Prior Scores Compromise Evaluation Independence

arXiv:2608.25869v1 Announce Type: new Abstract: Large language models (LLMs) increasingly assess generated content, giving rise to the LLM-as-a-Judge paradigm. These systems now score outputs, filter

Automatic weld seam segmentation for industrial quality control: a comparison of RGB and polarimetric imaging with CNN and transformer architectures

arXiv:2608.25465v1 Announce Type: new Abstract: Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the

Belief Cascades Drive Persuasion in LLM Agent Networks

arXiv:2608.25152v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly debate answers, coordinate research, simulate users, and mediate information flows, making agent-to-agent persuasio

Beyond Local Surprise: Grounded Dialogue as Selective Belief Revision under Referential Uncertainty

arXiv:2608.26035v1 Announce Type: new Abstract: When a speaker refers to a scene that the listener cannot directly see, the listener must decide whether to preserve its current understanding or revise

Boosting Reasoning in Large Multimodal Models via Activation Replay

arXiv:2511.19972v4 Announce Type: replace Abstract: Recently, Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach to incentivizing reasoning capability in Large

BVR Sim: An Open and High-Throughput Environment for Heterogeneous Air-Combat Reinforcement Learning

arXiv:2608.25419v1 Announce Type: cross Abstract: Beyond-visual-range (BVR) air combat is a challenging reinforcement-learning domain characterized by partial observability, long-horizon decision maki

CAT-GS: Balanced Multimodal Learning via Calibrated Gating and Fusion Surgery

arXiv:2608.24947v1 Announce Type: new Abstract: End-to-end training of multimodal neural networks often exhibits unstable neural dynamics characterized by three coupled failure modes that degrade lear

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future

Conditional Total Correlation and the Serial Depth of Adaptive Parallel Sampling

arXiv:2608.25505v1 Announce Type: cross Abstract: Motivated by parallel decoding in masked diffusion models, we study adaptive parallel sampling of discrete vectors: in each round, a deterministic pol

Context-Guided Semantic Alignment for Feature Fusion Networks

arXiv:2606.14005v2 Announce Type: replace Abstract: Feature fusion networks are fundamental components in modern object detectors, aggregating multi-scale features to detect objects of varying sizes.

Controllable Affective Generation via Latent Vector Steering

arXiv:2608.25569v1 Announce Type: new Abstract: Large Language Models (LLMs) often produce emotionally flattened responses after alignment, limiting their effectiveness in affect-sensitive application

Controlling for Omitted Variable Bias in Deep Neural Networks

arXiv:2608.25930v1 Announce Type: cross Abstract: Control variables are widely used in statistical modelling to account for omitted variable bias of known confounders. However, they have largely been

Cooperative Multi-Agent Reinforcement Learning for Adaptive Aggregation in Semi-Supervised Federated Learning with non-IID Data

arXiv:2608.25794v1 Announce Type: new Abstract: Federated Learning (FL) enables distributed training of machine learning models while preserving data privacy. However, FL struggles with heterogeneous,

D^3-MOPD: Adaptive Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation

arXiv:2608.24987v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence

DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand

Demystifying Reinforcement Learning Post-Training of Language Models

arXiv:2608.24949v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training has emerged as a powerful framework for enhancing the capabilities of large language models (LLMs), enabling

Deploy personal AI agents with Cloud Run instances

Need a low-cost, high-performance way to run long-lived, stateful workloads such as AI agents? Today, we introduced Cloud Run instances, which let you do just that. Consider AI agents such as OpenClaw

safetygoogle-cloud-ai

Diffusion Transformers for Roof Graph Synthesis and Reconstruction

arXiv:2608.25652v1 Announce Type: new Abstract: We present RoofDiT, a generative framework for 2D roof graph synthesis and reconstruction. Roofs are compactly described as planar graphs of junctions a

Distance Is Not Enough: Forget-Retain Alignment Gap Predicts LLM Relearning Robustness

arXiv:2608.25429v1 Announce Type: cross Abstract: Machine unlearning aims to make a model forget specific data, yet unlearned LLMs often fail to stay unlearned: brief fine-tuning can revive removed kn