Search: “models”

PolicyGuard: A Dialogue-Grounded Sub-Agent Verifier for Policy Adherence in LLM Agents

arXiv:2606.29225v1 Announce Type: new Abstract: LLM agents handle user requests on behalf of organizations through tool calls and must follow the company policies stated in their system prompts. Prior

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Pooled Leaderboards Hide System-Specific Winners: A Reporting-Protocol Audit of Offline Root-Cause Analysis Benchmarks

DGX agent

arXiv:2606.29159v1 Announce Type: new Abstract: Offline root-cause-analysis (RCA) benchmarks commonly rank methods by a single pooled top-1 accuracy across multiple subsystems, and engineers often rea

model-releasesarxiv-cs-ai

30 Jun 2026

Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy

arXiv:2606.28433v1 Announce Type: new Abstract: One goal in reinforcement learning (RL) research is to understand general-purpose sequential decision-making, using benchmark simulators as a proxy for

Post-training for Efficient Communication via Convention Formation

arXiv:2508.06482v2 Announce Type: replace-cross Abstract: Humans communicate with increasing efficiency in multi-turn interactions, by adapting their language and forming ad-hoc conventions. In contra

Projected Exploitability Descent for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games

arXiv:2606.29169v1 Announce Type: cross Abstract: Many important games have more than two players and imperfect information. Existing approaches for computing Nash equilibrium, the central game-theore

Proteus: Automated Adversarial Robustness Testing for Audio Deepfake Detectors

arXiv:2606.29544v1 Announce Type: cross Abstract: We present Proteus, a framework developed at Resemble AI for automated robustness testing of our audio deepfake detection system. Given a detector, Pr

Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification

arXiv:2606.29440v1 Announce Type: new Abstract: Repeatedly solving parametric PDEs is essential for uncertainty quantification, design optimization and inverse problems, but conventional neural operat

Reachability Guarantees for Cart-Pole Swing-Up and Stabilization

model-releasesarxiv-cs-ro

arXiv:2606.28627v1 Announce Type: cross Abstract: The cart-pole swing-up is a canonical benchmark for nonlinear control of underactuated systems, yet an end-to-end guarantee linking the global swing-u

Recursive Self-Evolving Agents via Held-Out Selection

arXiv:2606.28374v1 Announce Type: new Abstract: LLM agents are increasingly improved without weight updates by evolving a natural-language artifact, such as reflections, workflows, playbooks, cheatshe

Rehearsed Multi-Agent Live Product Demonstrations with Real-Time Voice Question Answering

arXiv:2606.30294v1 Announce Type: new Abstract: Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the correspo

Local Ai

Relevance Is Not Permission: Warranted Attention for Value Contributions

arXiv:2606.30139v1 Announce Type: new Abstract: Relevance is not permission. Attention lets a model read key-value items related to the current query, but it does not guarantee that the value contribu

local-aiarxiv-cs-ai

Research Entity Extraction and Topic Detection from UKRI Grant Proposals

arXiv:2606.30304v1 Announce Type: cross Abstract: This paper presents preliminary findings from a UKRI-funded Metascience project comparing three LLM-based approaches, GPT-4o, Mistral, and a bespoke a

Residual-Guided Dictionary Learning for Spectrally Accurate Koopman Approximation

arXiv:2606.29083v1 Announce Type: cross Abstract: Koopman theory promises linear structure in nonlinear dynamics, but numerical Koopman spectra are easy to compute and hard to trust. A finite EDMD mat

Resolution Thresholds in VLM Detection of Harmful ASCII Art Across Construction Modes and Languages

arXiv:2606.29649v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) are increasingly deployed as content moderation tools, yet they remain vulnerable to jailbreak attacks in which harm

safetyarxiv-cs-cl

Rethinking Forgery Attacks on Semantic Watermarks in Black-Box Settings: A Geometric Distortion Perspective

arXiv:2606.29807v1 Announce Type: cross Abstract: Recent studies have shown that semantic watermarks, which embed information into the initial noise of latent diffusion models (LDMs), are vulnerable t

Reweighting Framewise Attention in Video Transformers for Facial Expression Understanding

arXiv:2606.30611v1 Announce Type: new Abstract: Understanding facial expressions in videos requires modeling subtle and localized facial dynamics under unconstrained conditions. Although recent Vision

RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning

arXiv:2606.29867v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in robotics and autonomous systems, yet remains vulnerable to adversarial perturbat

SA-Homo: Scale Adaptive Homography Estimation for Scale Variation Scenarios

arXiv:2606.30408v1 Announce Type: new Abstract: Homography estimation, as one of the fundamental problems in computer vision, remains challenged by scale variation scenarios where image pairs potentia

Scalar Representations of Neural Network Training Dynamics

arXiv:2606.30384v1 Announce Type: new Abstract: Training in artificial neural networks can be viewed as a trajectory evolving through a high-dimensional loss landscape. However, the large number of tr

Scaling Textual Gradients via Sampling-Based Momentum

arXiv:2506.00400v4 Announce Type: replace-cross Abstract: LLM-based prompt optimization, which uses LLM-provided ``textual gradients'' (feedback) to refine prompts, has emerged as an effective method

Seed-to-Seed: Unpaired Image Translation in Diffusion Seed Space

arXiv:2409.00654v2 Announce Type: replace Abstract: We introduce Seed-to-Seed Translation (StS), a novel approach that combines GANs and diffusion models (DMs) for unpaired Image-to-Image Translation.

Selective Memory Retention for Long-Horizon LLM Agents

arXiv:2606.29178v1 Announce Type: new Abstract: When does retention matter for memory-augmented LLM agents? We study this with TraceRetain, a lightweight framework for bounded external memory in froze

Sequential Hiring of Contingent Workers Through Learning-Based Optimization

arXiv:2606.18438v2 Announce Type: replace-cross Abstract: In this paper, we study a sequential workforce management problem in a contingent labor setting with uncertainty in both worker production and

Sequential Planning via Anchored Robotic Keypoints

model-releasesarxiv-cs-ro

arXiv:2606.30613v1 Announce Type: new Abstract: We present Sequential Planning via Anchored Robotic Keypoints, SPARK, a training-free neurosymbolic manipulation system that reaches 43.7% on six LIBERO

SIGNET: Motion-Level Knowledge Transfer for Cross-Language Sign Language Translation

arXiv:2606.28626v1 Announce Type: new Abstract: Sign language translation (SLT) remains challenging due to its high spatio-temporal complexity, long sequences, and the need to model multiple articulat

SIR: Structured Image Representations for Explainable Robot Learning

arXiv:2606.30101v1 Announce Type: cross Abstract: Existing robot policies based on learned visual embeddings lack explicit structure and are sensitive to visual distractions. Thus, the representations

safetyarxiv-cs-cv

Situation Perception: A Necessary Primitive to Artificial Superintelligence

arXiv:2606.30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines. They compress vast amounts of text into useful patterns and can explain science,

researcharxiv-cs-ai

SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning

arXiv:2602.02472v2 Announce Type: replace-cross Abstract: Progressive Learning (PL) reduces pre-training computational overhead by gradually increasing model scale. While prior work has extensively ex

Spectral phase transitions and trainability in neural network learning dynamics

arXiv:2606.28486v1 Announce Type: cross Abstract: The emergence of low-dimensional structures in the spectra of neural network weight matrices is a common empirical feature of trained models, but the

safetyarxiv-cs-lg

SWE-Together: Evaluating Coding Agents in Interactive User Sessions

arXiv:2606.29957v1 Announce Type: cross Abstract: Most coding-agent benchmarks are static: an agent receives a complete task description up front and is judged only by its final code. Real coding assi

The Effect of Scripts and Formats on LLM Numeracy

arXiv:2601.15251v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive proficiency in basic arithmetic, rivaling human-level performance on standard numerical tasks.

The Platonic Defense: Backdoor Defense for Self-Supervised Encoders in the Era of Large Scale Pre-training

arXiv:2606.29451v1 Announce Type: new Abstract: Self-supervised learning (SSL) pretrained models have become a dominant paradigm for visual representation learning, but they are vulnerable to backdoor

Tool Use Enables Undetectable Steganography in Multi-Agent LLM Systems

arXiv:2606.28425v1 Announce Type: cross Abstract: Increasingly autonomous agentic AI systems pose novel multi-agent risks, such as secret collusion via covert communication channels. The natural defen

safetyarxiv-cs-ai

Toward an Energy-Optimized Operation of Data Centers Located in Wind Farms Using Reinforcement Learning

arXiv:2606.30316v1 Announce Type: new Abstract: This paper studies Reinforcement Learning as an online controller for curtailment-aware workload shifting in wind-turbine-integrated high-performance co

Towards in-the-wild Egocentric 3D Hand-Object Pose Estimation

arXiv:2606.30598v1 Announce Type: new Abstract: Estimating accurate 3D hand-object pose from in-the-wild egocentric RGB remains challenging due to severe occlusions and ambiguous contact. Existing lea

Vivid-VR: Distilling Concepts from Text-to-Video Diffusion Transformer for Photorealistic Video Restoration

arXiv:2508.14483v4 Announce Type: replace Abstract: We present Vivid-VR, a DiT-based generative video restoration method built upon an advanced T2V foundation model, where ControlNet is leveraged to c

safetyarxiv-cs-cv

wav2VOT: Automatic estimation of voice onset time, closure duration, and burst realisation with wav2vec2

arXiv:2606.28857v1 Announce Type: cross Abstract: While automatic tools for speech annotation are now commonplace within phonetic research pipelines, many tasks require substantial manual correction o

When Can Conformal Risk Control Certify LLM Outputs? Bounds, Impossibility, and Adaptation for Structured Generation

arXiv:2606.29054v1 Announce Type: new Abstract: Large language models (LLMs) deployed for structured generation (NER, JSON extraction, QA, and classification) lack formal reliability guarantees, and s

researcharxiv-cs-lg

Agents

When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis

arXiv:2606.29251v1 Announce Type: new Abstract: Financial decision-makers face more information than they can directly inspect, making context compression necessary. Yet when large language models (LL

agentsarxiv-cs-ai

Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy

arXiv:2606.29489v1 Announce Type: new Abstract: When humans translate, not every word depends equally on the surrounding context. Some tokens, particularly function words like pronouns and auxiliaries

Whose Side Is Your Agent On? Multi-Party Principal Loyalty in LLM Agents

arXiv:2606.30383v1 Announce Type: new Abstract: A rapidly growing class of LLM agents is multi-party: the agent acts for a principal (who briefs it, sends follow-ups, and receives results) while also

XYZ-IBD: Benchmarking Robust 6D Object Pose Estimation under Real-World Industrial Complexity

arXiv:2506.00599v3 Announce Type: replace Abstract: While current 6D pose estimation benchmarks have reached near-saturation on household objects, they often fail to capture the stochastic and optical

Zero-Shot Depth from Defocus

arXiv:2603.26658v2 Announce Type: replace Abstract: Depth from Defocus (DfD) is the task of estimating a dense metric depth map from a focus stack. Unlike previous works overfitting to a certain datas

Agentic Hardware Design as Repository-Level Code Evolution

arXiv:2606.28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled int

ATOD: Annealed Turn-aware On-policy Distillation for Multi-turn Autonomous Agents

arXiv:2606.27814v1 Announce Type: new Abstract: Training small language-model agents for long-horizon interactive tasks requires both fast imitation and reward-driven improvement. On-policy distillati

safetyarxiv-cs-ai

Aurora: A Leverage-Aware Spectral Optimizer

arXiv:2606.27715v1 Announce Type: new Abstract: We show that for tall matrix parameters, like projection matrices in the MLP layers, the Muon update can have row norms that are arbitrarily non-uniform

Autoencoder Architectures for Athlete Performance Scoring from Wearable Telemetry

arXiv:2606.28145v1 Announce Type: new Abstract: Wearable devices produce large, high dimensional training logs for everyday runners, and interpretation rather than data collection is now the limiting

researcharxiv-cs-lg

Local Ai

Beyond Sequential Distance: Inter-Modal Distance Invariant Position Encoding

arXiv:2603.10863v2 Announce Type: replace Abstract: Despite the remarkable capabilities of Multimodal Large Language Models (MLLMs), they still suffer from visual fading in long-context scenarios. Spe

local-aiarxiv-cs-cv