Search: “benchmark”

Automatic Harness Evolution for Hardware Design Verification: Can LLMs Consolidate Gains Across Discovered Harnesses?

arXiv:2609.28908v1 Announce Type: cross Abstract: Agent behavior depends on the harness surrounding a language model, but it remains unclear whether language models can reliably improve such harnesses

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Back to the Definition: Estimating Step-Level Advantages via Trajectory Graphs for Agentic Reinforcement Learning

DGX agent

arXiv:2609.28963v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) methods, such as GRPO and its variants, have become a leading paradigm for training reasoning and agentic large

safetyarxiv-cs-ai

25 Sept 2026

Banger paper from Microsoft and colleagues. We talk about human taste being important in this AI era. But for recursive self-improvement, an…

Banger paper from Microsoft and colleagues. We talk about human taste being important in this AI era. But for recursive self-improvement, an agent's taste also matters. The big question is: How often

model-releasesdair-ai--x

Baszta: Data-Centric Fine-Tuning of a Polish Multi-Label Safety Classifier

arXiv:2609.29266v1 Announce Type: new Abstract: We develop a multi-label Polish content-safety classifier by fine-tuning allegro/herbert-base-cased (124M) across five categories (hate, vulgarity, sexu

Hardware

Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers

arXiv:2609.30198v1 Announce Type: new Abstract: Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent sp

hardwarearxiv-cs-lg

Beyond Pairwise Attention: Higher-Order Modular Attention for Efficient Sequence Learning

arXiv:2603.11133v2 Announce Type: replace Abstract: Sequence modeling tasks can involve intrinsic higher-order dependencies, while standard self-attention assigns scores to token pairs and does not ex

Beyond Surface Style: Aligning Multi-Turn User Simulators with Behavioral Consistency

arXiv:2609.28690v1 Announce Type: new Abstract: Faithful user simulation is fundamental to building, evaluating, and improving interactive AI at scale. However, plausible individual responses do not e

BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion

arXiv:2609.29487v1 Announce Type: new Abstract: Knowledge graph completion models optimize ranking, although many downstream applications require calibrated probabilities. We present BLADE, a variatio

researcharxiv-cs-lg

BridgeMem: Causal Dyadic Transition Residuals for Temporal Knowledge Graph Forecasting

arXiv:2609.29268v1 Announce Type: new Abstract: Temporal knowledge graph forecasting aims to infer future relational facts from the temporal structure of observed events. Existing forecasters mainly s

researcharxiv-cs-lg

Agents

Calibrated Decision Models for Autonomous Penetration-Testing Harnesses: JEV and Laya as System One Decision Layers for LLM-Driven Pentest Agents

arXiv:2609.28940v1 Announce Type: cross Abstract: Autonomous penetration-testing harnesses use large language models (LLMs) for reconnaissance, exploitation, and reporting, but often rely on those sam

agentsarxiv-cs-ai

Can Classical Semantic-Extractive Summarization Be Evaluated in Hindi? A Replication Study

arXiv:2609.29090v1 Announce Type: cross Abstract: We replicate the distributional-semantics extractive summarisation method of Mohd, Jan and Shah (2020) and adapt it to Hindi, substituting a Devanagar

researcharxiv-cs-ai

Coding Agents for Generalized Task and Motion Planning Problems

arXiv:2609.30233v1 Announce Type: cross Abstract: Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightl

Combining Evasive and Braking Reactions for Safety Reference Models in Automated Vehicles

arXiv:2609.29738v1 Announce Type: new Abstract: Computational models of careful and competent human drivers are essential for scenario-based evaluation of automated driving systems (ADS). However, mos

safetyarxiv-cs-ro

ComplexSync: High-Fidelity and Real-Time Lip Sync in Complex Scenarios

arXiv:2609.29225v1 Announce Type: new Abstract: Lip synchronization aims to generate visual lip dynamics that align precisely with speech audio. Despite the high generation quality of diffusion models

Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

arXiv:2609.29194v1 Announce Type: cross Abstract: Mobile robots require robust, real-time fault detection capable of continuous adaptation on constrained edge hardware. While deep time-series models e

Decoupled Early Exits for Task-Dependent Compute Allocation in Flow-Matching VLAs

arXiv:2609.29382v1 Announce Type: cross Abstract: Flow-matching Vision-Language-Action (VLA) models have emerged as a potential solution for generalist robot control, designed by combining a pretraine

safetyarxiv-cs-lg

Don't Read the Log: Execution Traces Contaminate Verifiers in Video-Generation Agents

arXiv:2609.28564v1 Announce Type: cross Abstract: Agentic video-generation systems close a loop between a generator and a verifier: an LLM plans shots, calls a text-to-video model, and a multimodal ju

Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

arXiv:2609.29096v1 Announce Type: new Abstract: Post-hoc correction adjusts a forecaster that cannot be retrained, such as a foundation model, but a correction fitted where errors are stable can hurt

safetyarxiv-cs-lg

Agents

Dual-Frontier: When Can an Agent Trust Its World Model?

arXiv:2609.26293v2 Announce Type: replace Abstract: Learned world models are becoming essential to general-purpose agents: by predicting action consequences, they support planning and decision-making

agentsarxiv-cs-ai

EAGER: Enhancing Generative Event Extraction via Reinforcement Learning with Verifiable Rewards

model-releasesarxiv-cs-cl

arXiv:2609.29230v1 Announce Type: new Abstract: End-to-end event extraction remains challenging for large language models as it requires simultaneous identification of event triggers, classification o

Tutorials

EIB-Net: Entropy-Guided Information Bottleneck for Generalizable AI-Generated Image Detection

arXiv:2609.29064v1 Announce Type: cross Abstract: The proliferation of photorealistic AI-generated images demands robust detection methods that generalize across diverse generative models. While exist

tutorialsarxiv-cs-ai

Encoded but Not Decoded: Layer-Localized Evidence for a Three-Level Gap in LLM Syntax

model-releasesarxiv-cs-cl

arXiv:2609.29848v1 Announce Type: new Abstract: A language model can fail a syntactic test in two distinct ways: by not encoding the relevant structure, or by encoding it but failing to use it at the

EndoFSA: Endoscopic Few-Shot Image Generation via Rank-Constrained Parameter Adaptation

arXiv:2609.29930v1 Announce Type: new Abstract: WCE produces large-scale gastrointestinal image data yet pathological findings remain significantly underrepresented limiting the generalization perform

Evaluating Explanation-Driven Vision-Language Reasoning via Generation Order Interventions

arXiv:2609.29496v1 Announce Type: new Abstract: Natural language explanation generation serves as a key mechanism for exposing and evaluating vision-language reasoning. Prior work on explanation-drive

researcharxiv-cs-cl

ExplorationBench: Measuring AI Systems' Exploration in Verifiable Alien Worlds

arXiv:2609.30199v1 Announce Type: new Abstract: Scientific discovery begins where known problems end. There, AI systems must engage in exploration: framing hypotheses, designing experiments, and itera

Faster Visuomotor Policy Learning on Action Manifolds via Riemannian MeanFlow

arXiv:2609.30127v1 Announce Type: new Abstract: Visuomotor policies learn a direct map from raw sensory observations to robot action sequences. Policies based on Diffusion and Flow Matching capture th

safetyarxiv-cs-ro

Free the Language Model From the Vision Encoder: Semantic Serialization as a Perception Interface for Small Language Models

model-releasesarxiv-cs-cl

arXiv:2609.29601v1 Announce Type: cross Abstract: End-to-end vision-language models (VLMs) bind visual competence to the scale of their language model: as the language model shrinks, perception and re

From Static Personal Values to Contextualized Personalization: Bayesian Personalized Value Alignment for LLMs

arXiv:2609.28942v1 Announce Type: new Abstract: Personalized value alignment has become increasingly important as large language models (LLMs) are expected to accommodate diverse user preferences. How

safetyarxiv-cs-ai

From Text Decisions to Pixels: An Study of Jev-Style Visual Choice Model

arXiv:2609.29283v1 Announce Type: new Abstract: Visual software often needs a decision over supplied alternatives rather than a generated explanation. We present PixelJev, a native-image decision inte

GBFRVFL: Granular-Ball Computing-Based Fuzzy Random Vector Functional Link Network

arXiv:2609.29670v1 Announce Type: new Abstract: In practical machine learning tasks, data are often contaminated with noise, outliers, and class imbalance, which can degrade the performance of convent

Hardware

GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS

arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving

hardwarearxiv-cs-ai

GPT-6-Astra Lights Up Embodied Navigation: Evaluation in Zero-Shot Vision-and-Language Navigation in Continuous Environments

model-releasesarxiv-cs-ro

arXiv:2609.29861v1 Announce Type: new Abstract: We investigate whether GPT-6-Astra, a general-purpose foundation model, can navigate unfamiliar environments using its own perception, reasoning, and de

Grow the Harness, Not the Context: From Strategy-Free Scaffolds to Reusable Specialist Agents

arXiv:2609.26760v2 Announce Type: replace Abstract: Large language model (LLM) agents often handle streams of related tasks, yet standard harnesses repeatedly ask the model to reconstruct the same con

HClimRep-Ocean: A Global Ocean Emulator on an Unstructured Mesh

arXiv:2609.28601v1 Announce Type: cross Abstract: Machine-learning (ML) emulators for atmospheric processes have advanced rapidly in recent years, transforming weather forecasting. Although early ML o

iCoder-27B: Recursive AI-Led Development of Frontier Industrial Coding Model

arXiv:2609.29626v1 Announce Type: new Abstract: Recursive AI, the prospect of AI taking an increasingly complete role in building and improving AI, is a crown jewel of AI for AI. Although recursive se

IndicBankBench: Evaluating Safety and Reliability of Language Model Assistants in Indian Retail Banking

arXiv:2609.29167v1 Announce Type: new Abstract: Banking assistants must use account-specific information to answer requests and, in many cases, take actions through tools. Evaluating only the final re

Industrial Anomaly Detection via Defect-Grounded Reasoning in Visual Latent Space

arXiv:2609.29457v1 Announce Type: new Abstract: Industrial anomaly detection (IAD) is evolving beyond conventional detection and localization toward multimodal inspection systems that can describe, ex

Instrumental Monitor Evasion Emerges Under Ordinary Task Pressure

arXiv:2609.30217v1 Announce Type: cross Abstract: A central concern in AI safety is that agents may treat oversight as an obstacle when it conflicts with completing their goals. We study instrumental

Interpretable Similarity of Synthetic Image Utility

arXiv:2512.17080v2 Announce Type: replace Abstract: Synthetic medical image data can unlock the potential of deep learning (DL)-based clinical decision support (CDS) systems through the creation of la

IterSynth: Rethinking Deep Search Agents via Role-Decoupled Iterative Synthesis

arXiv:2609.29444v1 Announce Type: cross Abstract: Deep search requires LLM agents to decompose complex queries, search for evidence, and synthesize grounded answers, yet existing ReAct-style agents su

safetyarxiv-cs-ai

Jev vs. Kev: open-source Jev alternative tested side by side

model-releasesr-localllama

We hosted Kev 4B (Jared Palmer's Apache-2.0 fine-tune of Qwen3.5-4B) and ran it side by side with Jev on the same endpoint to see how it compares. We built a fresh set of 362 items published after bot

JEV vs. LLMs as Rubric Judges: Cheaper, Faster, and Wrong in the Same Places

arXiv:2609.29769v1 Announce Type: new Abstract: We ask whether Jev, a typed classifier that returns probabilities over permitted answers without generating text, can replace an LLM rubric judge. We co

researcharxiv-cs-cl

KeyGen: Unsupervised Keypoint based Object-Centric Representations for Category-Level Policy Generalization

arXiv:2609.28818v1 Announce Type: cross Abstract: Generalization in robotic manipulation requires policies to perform tasks across diverse unseen object instances that vary in shape, size, and pose. H

Learning a Flow to Self-Supervised Representations

arXiv:2609.29350v1 Announce Type: new Abstract: Explicit geometric references offer a direct way to structure self-supervised representations. Existing adversarial distribution-matching formulations,

safetyarxiv-cs-cv

Learning Better Reasoning for Generative Recommendation with Semantic IDs

arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'

safetyarxiv-cs-ai

Tutorials

Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

tutorialsarxiv-cs-lg

LLM on a budget part 2, from P102-100 to CMP 50HX.

model-releasesr-localllama

I finally got around to upgrade the GPU's. First a word of warning, when upgrading GPU's on P520 you have to be extra careful not to slot the card on any angle other than straight when installing or w

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their