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Rolling With Resistance: Preference-Optimized LLM Counselors Can Trade Goal Persistence for Relational Attunement in Motivational Interviewing

arXiv:2607.28814v1 Announce Type: cross Abstract: In Motivational Interviewing (MI), a client's sustain talk (arguments for the status quo) calls for the counselor to roll with resistance, a move that

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Safety

RTLCurator: Label-Efficient Data Curation for RTL Generation

DGX agent

arXiv:2607.29283v1 Announce Type: cross Abstract: Training large language models (LLMs) to write register-transfer level (RTL) requires large corpora of paired specifications and code, and such data i

safetyarxiv-cs-lg

3 Aug 2026

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

model-releasesarxiv-cs-ro

arXiv:2607.17977v2 Announce Type: replace Abstract: We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and p

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco

Safe Vision Language Action Models via Barrier Enhanced Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.29569v1 Announce Type: new Abstract: This article presents a modular inference framework that integrates Flow Matching generative models with formal Control Barrier Function (CBF) safety gu

Local Ai

SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs

arXiv:2607.28969v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes

local-aiarxiv-cs-cv

Safety, or Just Capability? A Validity Audit of Agent-Safety Benchmarks

arXiv:2607.28685v1 Announce Type: new Abstract: Agent-safety benchmarks measure different behaviors, and their scores get quoted interchangeably as an agent's safety. We treat four of them (R-Judge, I

SAGP: Semantic Affordance-Guided Grasp Planning via Coarse-Zone VLM Reasoning

arXiv:2607.29374v1 Announce Type: new Abstract: Geometry-based grasp planners ensure physically valid grasps but ignore functional semantics, often generating grasps that are antipodal and collision-f

safetyarxiv-cs-ro

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting

arXiv:2607.29033v1 Announce Type: new Abstract: Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or req

Sample Efficient Hierarchical Reinforcement Learning via Best Policy Identification

arXiv:2607.29294v1 Announce Type: new Abstract: We present HBPI-UCRL, a model-based algorithm for hierarchical reinforcement learning (HRL) that learns high-level and low-level policies in parallel. H

safetyarxiv-cs-lg

SatEdit: Mask-Conditioned Image Editing via VLM-Guided Segment Annotation

arXiv:2607.29367v1 Announce Type: new Abstract: Satellite image editing requires spatially precise object-level control, but supervised editing datasets for overhead imagery are costly to build becaus

safetyarxiv-cs-cv

SATViz: Real-Time Visualization of Clausal Proofs

arXiv:2209.05838v2 Announce Type: replace Abstract: Visual layouts of graphs representing SAT instances can highlight the community structure of SAT instances. The community structure of SAT instances

Scaffolding Critical Engagement with GenAI: Transforming Ethnic Minority Preparatory Students' Collaborative Discourse in Prompt Engineering Tasks

arXiv:2607.28630v1 Announce Type: cross Abstract: Generative AI (GenAI) holds significant promise for advancing educational equity among ethnic minority students by broadening access to learning resou

Scaling Properties of Text Conditioning in Visual Generation

arXiv:2607.29679v1 Announce Type: new Abstract: We study empirical scaling properties for text conditioning in visual generation. Such properties have rarely been measured because diffusion loss does

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

agentsarxiv-cs-ai

SciFigPlag-Bench: A Benchmark for Provenance-Aware Scientific Figure Plagiarism Detection

arXiv:2607.29124v1 Announce Type: new Abstract: Scientific figures often encode the visual evidence behind scientific findings, yet figure plagiarism remains underexplored as a benchmarked multimodal

SciToolAgent-Evo: An Ontology-Aware Self-Evolving Agent for Open-World Scientific Tool Acquisition

arXiv:2607.28692v1 Announce Type: new Abstract: Large language model (LLM) agents have been increasingly adopted in scientific research for organizing and invoking specialized computational tools. How

SCMA: Structure-Conditioned and Metal-Aware Flow Matching for CT Metal Artifact Reduction

arXiv:2607.28759v1 Announce Type: cross Abstract: In X-ray CT, metallic objects cause beam hardening, photon starvation, and scattering, leading to projection inconsistency, streaks, dark bands, and s

SEDR-Seq2P: A Lightweight Dilated Residual Sequence-to-Point Network for Multi-Task Industrial NILM

arXiv:2607.28693v1 Announce Type: cross Abstract: Industrial NILM remains challenging because measurement noise and widespread concurrent machine operation reduce the generalization of models tuned on

Seeing Differently: Modeling Interpretive Perspectives in Computational Creativity using a Four-World Framework

arXiv:2607.28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks a

SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery

arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic

Self-Play Meets Skill Evolution: Self-Evolving Search Agents that Pose, Solve, and Remember

arXiv:2607.29468v1 Announce Type: new Abstract: Self-play agents can generate training problems without questions from target benchmarks, but their curricula lack persistent state: failures affect gra

Self-Supervised Skill Optimization

arXiv:2607.28777v1 Announce Type: new Abstract: Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized

agentsarxiv-cs-cl

Applications

Semantics of Subterfuge: Benchmarking Legal Deception Detection Against General-domain State-of-the-Art

arXiv:2607.29066v1 Announce Type: cross Abstract: Deception detection has critical implications for legal proceedings, law enforcement, and online security. Although human judgment is limited in accur

applicationsarxiv-cs-ai

Sensitivity Analysis of GRU, LSTM and Transformer Encoder in Classification of Automated Driving Systems

arXiv:2607.28665v1 Announce Type: cross Abstract: Automated driving systems (ADSs) are becoming ubiquitous. Future Software Defined Vehicles (SDVs) may be able to run multiple ADSs, both native and af

SERUM: State Extraction and Refinement for User Modeling

arXiv:2607.29181v1 Announce Type: cross Abstract: Agentic assistants capable of proactive, personalized interactions require structured models of user intent and workflow. However, building these mode

agentsarxiv-cs-ai

Shall We Play a Game? Language Models for Open-ended Wargames

arXiv:2509.17192v3 Announce Type: replace Abstract: LLM-based social simulations can make a generated transcript look like a single behavioral signal, but the model behind that transcript may be doing

Shaping Scientific Explanations to Expert Perspectives with Persona-Conditioned Reinforcement Learning

arXiv:2603.21846v2 Announce Type: replace Abstract: Explainable AI is increasingly important to scientific discovery. However, existing methods largely ignore that explanation quality is not universal

agentsarxiv-cs-ai

Shapley-Value-Based Feature Attribution for Data Masking

arXiv:2607.28946v1 Announce Type: new Abstract: Despite its many benefits, widespread access to individuals' personal data also causes severe privacy concerns for consumers, companies, and policymaker

Side-Channel Attacks Survive Noise Cancellation in 3D Printers

arXiv:2606.13952v2 Announce Type: replace-cross Abstract: Active Motor Noise Cancellation (AMNC) is a noise-reduction feature shipped in commercial fused deposition modeling (FDM) 3D printers. Because

Sign compression for Muon: SignMuon, MuonSign, and the Limits of Error Feedback

model-releasesarxiv-cs-lg

arXiv:2607.29674v1 Announce Type: cross Abstract: SignMuon compresses the Muon update to one bit per parameter by taking its elementwise sign, providing the most direct way to run a matrix-aware optim

SILVA Networks as Structured Implicit Layers and Vector Attractors via Dynamic Interaction Fields

model-releasesarxiv-cs-lg

arXiv:2607.28989v1 Announce Type: new Abstract: Many learning problems require representations that reconcile direct input, nearby structure, and broader context. In implicit neural layers, these infl

Simple-regret rates and minimax optimality of fixed-prior expected improvement in Matern and squared-exponential RKHSs

arXiv:2607.29245v1 Announce Type: cross Abstract: We study the expected improvement (EI) policy for minimizing a deterministic objective function f on a nonempty compact set mathcal X subsetmathbb R^d

safetyarxiv-cs-lg

Simulation Code Generation for Fluid Systems using Large Language Models: Benchmarking Models and Prompting Strategies

model-releasesarxiv-cs-lg

arXiv:2607.29389v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated a strong ability to generate syntactically correct code from natural-language specifications. In this stu

Simulative Anomaly Detection using 2D Tomography

arXiv:2607.28701v1 Announce Type: cross Abstract: We present a novel technique for predicting the imaging quality of anomalies such as cancer cells located inside organic tissues. This technique is us

researcharxiv-cs-cv

Local Ai

Small Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters

arXiv:2607.29238v1 Announce Type: cross Abstract: InMyStyle is a privacy first, single user system that adapts small language models to rewrite AI-edited text towards an individual user's writing styl

local-aiarxiv-cs-ai

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

arXiv:2505.18660v5 Announce Type: replace Abstract: Recent advances in AI-powered generative models have enabled the creation of increasingly realistic synthetic images, posing significant risks to in

SPICE: Synergy and Partial Information Based Curriculum Evolution

arXiv:2606.16639v2 Announce Type: replace Abstract: Multimodal learning exploits complementary information across heterogeneous modalities. The informativeness of each modality can vary widely across

Applications

ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts

arXiv:2607.28993v1 Announce Type: cross Abstract: World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance

applicationsarxiv-cs-cv

Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens

arXiv:2607.29363v1 Announce Type: cross Abstract: Balancing sequence length, representational capacity, and long-horizon stability is a central problem in autoregressive (AR) speech and audio generati

STAGE: STyle-controllable Action GEneration for personalized autonomous driving

arXiv:2607.29517v1 Announce Type: new Abstract: Driving style refers to the behavioral preferences that drivers maintain during driving, shaped by their diverse experiences, habits, and needs, and is

safetyarxiv-cs-ro

StaQ: a Finite Memory Approach to Discrete Action Policy Mirror Descent

arXiv:2506.13862v2 Announce Type: replace-cross Abstract: In Reinforcement Learning (RL), regularization with a Kullback-Leibler divergence that penalizes large deviations between successive policies

Stem: Rethinking Causal Information Flow in Sparse Attention

arXiv:2603.06274v2 Announce Type: replace-cross Abstract: The quadratic computational complexity of self-attention remains a fundamental bottleneck for scaling Large Language Models (LLMs) to long con

Step-Level Visual Grounding Faithfulness Predicts Out-of-Distribution Generalization in Long-Horizon Vision-Language Models

arXiv:2603.06828v2 Announce Type: replace-cross Abstract: We uncover a behavioral law of long-horizon vision-language models: models that maintain temporally grounded beliefs generalize better. Standa

StraightDP: Geometry-Aware Differential Privacy for Rectified-Flow Transformers

arXiv:2607.29100v1 Announce Type: cross Abstract: Differentially private (DP) training of text-conditioned generative models suffers a utility cliff at strong privacy. We revisit this problem through

Stratified Negation in RDF Rules: A Correct Approach (Extended Version)

arXiv:2607.28778v1 Announce Type: cross Abstract: Combining RDF rule languages, such as N3 or SHACL Rules, with default negation is challenging. Existing methods to stratify negation often fail for RD

Structured Neural Chaos: An Adaptive Surrogate Modeling Framework for Functional Uncertainty Quantification and Global Sensitivity Analysis

arXiv:2607.28903v1 Announce Type: cross Abstract: Variance-based global sensitivity analysis (GSA) plays a key role in uncertainty quantification by identifying the contributions of uncertain inputs t

Hardware

Studying quantization trade-offs for efficient inference deployment in machine translation

arXiv:2607.29397v1 Announce Type: new Abstract: Deploying large language models in realistic server environments poses challenges, as the system needs to provide high-quality responses with low latenc

hardwarearxiv-cs-cl