Search: “benchmark”

Form Over Content In Gradient-Based Data Attribution Methods

arXiv:2609.19589v1 Announce Type: cross Abstract: Data attribution methods using gradient similarity are widely used to analyze and select training data for large language models, but what gradient si

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Self Improvement via Fast Tree-search

DGX agent

arXiv:2609.19526v1 Announce Type: new Abstract: Coding agents can recursively modify their own implementations, forming a loop of self-improvement. While prior work shows this can boost performance on

model-releasesarxiv-cs-ai

18 Sept 2026

The Environmental Impacts of Language Model Training Keep Rising Now is the Time to Catch Impacts on the Rebound

arXiv:2510.09022v2 Announce Type: replace Abstract: Recent Machine Learning (ML) approaches have shown increased performance on benchmarks at the cost of escalating compute demands. Hardware, algorith

researcharxiv-cs-lg

TripScore: Aligning LLMs for Real-World Travel Planning via Expert-Calibrated Reward

arXiv:2510.09011v4 Announce Type: replace Abstract: In our deployed travel-planning service, most users give minimal inputs or free-form requests rather than the structured constraint checklists assum

When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models

arXiv:2603.26556v3 Announce Type: replace-cross Abstract: Converting a pretrained Transformer into a more efficient hybrid model through distillation offers a promising approach to reducing inference

A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios

arXiv:2505.07622v2 Announce Type: replace Abstract: Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metri

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

arXiv:2609.18123v1 Announce Type: new Abstract: Large language model agents tune GPU kernels and serving engines through a closed loop of propose, measure, and keep, but the measurements behind this l

Beyond Routine Compliance: Cunning Data Cultivates Safety Vigilance in Large Language Models

arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm

CANTABILE: Learning Expressive Dynamics for Robotic Piano Performance

model-releasesarxiv-cs-ro

arXiv:2609.18213v1 Announce Type: new Abstract: Robotic piano playing has emerged as a standard benchmark for dexterous bimanual manipulation, yet progress on it has been measured almost entirely by n

Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden

Do Frontier Models Seek Safety Evidence Before Acting?

arXiv:2609.17865v1 Announce Type: new Abstract: Frontier models are often evaluated on how they respond to safety information once it is already in context. We study an earlier decision point: whether

Echo: Learning-based Matching Decompilation using Trusted Back Translation

arXiv:2609.18706v1 Announce Type: cross Abstract: Neural decompilers can recover readable and recompilable source code from binaries, but their predictions remain difficult to trust. Matching decompil

EDCT-Bench: Uncovering Faithfulness Gaps in VLMs via Explanation-Driven Counterfactual Testing

arXiv:2609.17953v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can produce Natural Language Explanations (NLEs) that sound plausible yet remain inconsistent with the visual evidence t

English Word Sense Disambiguation in 2026: When the Labels Become the Bottleneck

arXiv:2609.17554v1 Announce Type: new Abstract: In English all-words word sense disambiguation (WSD), the labels, not the models, have become the bottleneck: frontier LLMs are accurate enough that the

ERPBench: A State-Grounded Evaluation Paradigm for Computer-Use Agents in Enterprise Software

arXiv:2609.17885v1 Announce Type: new Abstract: Computer-use agents that operate through screenshots and simulated actions are advancing rapidly, yet their evaluation remains anchored to general deskt

GeoCueFormer: Geometry-Guided Wavelet Representation and Prediction-Cued Dual-Stage Decoder for Underwater Semantic Segmentation

arXiv:2609.18069v1 Announce Type: new Abstract: Underwater semantic segmentation is essential for marine ecosystem monitoring, yet remains challenging due to severe visual degradation. Light absorptio

HPOQuest: A Rare-Disease Diagnostic Agent Using Active Phenotype Acquisition

arXiv:2609.18431v1 Announce Type: new Abstract: More than 300 million people worldwide are affected by one of over 7,000 known rare diseases, yet diagnosis remains difficult because patients initially

PersonaPath: Towards Knowledge-Centric Personalized Learning Path Planning

arXiv:2609.18861v1 Announce Type: new Abstract: Adaptive learning systems commonly formulate learning path planning as Exercise-Centric (EC) recommendation, where the next step is inferred from item-l

Structured Claim-Level Discourse Representations for Dense Health Narratives

arXiv:2609.18905v1 Announce Type: new Abstract: Health discourse in social media videos often contains densely entangled claims spanning multiple thematic aspects, stances, evidential frames, and rhet

SurgRAW: Multi-Agent Workflow with Chain of Thought Reasoning for Robotic Surgical Video Analysis

arXiv:2503.10265v3 Announce Type: replace Abstract: Robotic-assisted surgery (RAS) is central to modern surgery, driving the need for intelligent systems with accurate scene understanding. Most existi

Visual Autoregressive Priors for RAW-to-sRGB Image Signal Processing

arXiv:2609.18302v1 Announce Type: new Abstract: RAW-to-sRGB image signal processing (ISP) must recover perceptually faithful colors and fine details from sensor measurements, often under imperfect spa

Which LLM is Best for Translating Natural Language Goals to PDDL

arXiv:2609.18731v1 Announce Type: new Abstract: Bridging the gap between human intent and machine execution remains a challenge in automated planning, where expressing goals in formal languages like P

AquiLLM: Evaluating Faithfulness in Open-Weight RAG-LLM Systems for Scientific Research

arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that p

Assurance Envelopes for Autonomous Coding Agents: Minimum-Cost Evidence for Software Change

arXiv:2609.16302v1 Announce Type: cross Abstract: When a coding agent returns to existing software, it inherits evidence from earlier engineering work: tests, type checks, proofs, static analyses, and

Audio-Visual Turn-taking Prediction in Cocktail Party Scenarios

arXiv:2609.17056v1 Announce Type: cross Abstract: Current predictive turn-taking models (PTTMs) achieve strong performance on benchmarks with controlled acoustic conditions and clean audio signals. Th

researcharxiv-cs-cl

CLIP Embeddings for AI-Generated Image Detection: A Few-Shot Study with Lightweight Classifier

arXiv:2505.10664v2 Announce Type: replace-cross Abstract: Verifying the authenticity of AI-generated images presents a growing challenge on social media platforms these days. While vision-language mod

GeoLAM: Learning Geometry-Grounded Latent Actions from Unlabeled Human Videos

arXiv:2609.17099v1 Announce Type: new Abstract: Human videos provide rich manipulation experience, but extracting action representations that preserve useful motion remains challenging. Visual reconst

MUUNRiver-Bench: Diagnosing Relation-Dependent Music Retrieval with Multimodal Instructions

arXiv:2609.16090v1 Announce Type: cross Abstract: Music retrieval is relation-dependent: given a reference track, a listener may seek its style with a new theme, a cover, or a comparable voice, and th

Neuro-Symbolic Hierarchical Intention Anticipation in Human Behavior

arXiv:2609.17064v1 Announce Type: new Abstract: Assistive autonomous systems must anticipate human goals before an observed behavior is complete. This article formulates anticipation as goal inference

Safety

Position: AI Is Not Ready for Strategic Conflicts

arXiv:2609.16189v1 Announce Type: new Abstract: Open-ended strategic wargames are high-stakes LM-based social simulations: they model adversaries, institutions, escalation, plan brittleness, doctrine,

safetyarxiv-cs-ai

Predicting Human Disagreement for Calibrated Dynamic Facial Expression Recognition

arXiv:2609.17130v1 Announce Type: new Abstract: Dynamic facial expression recognition (DFER) benchmarks such as DFEW provide multiple annotator votes per clip, yet most models collapse them to a major

researcharxiv-cs-cv

RAM-H1200: A Unified Evaluation and Dataset on Hand Radiographs for Rheumatoid Arthritis

arXiv:2605.05616v2 Announce Type: replace Abstract: Rheumatoid arthritis (RA) assessment from hand radiographs requires multi-level analysis and modeling of anatomical structures and fine-grained loca

RegRet: Enhancing Region-Level Retrieval in Large Multimodal Models

arXiv:2609.16847v1 Announce Type: cross Abstract: Region-level retrieval aims to align user-specified image regions with relevant regions or textual descriptions, playing a crucial role in realworld a

TEDi: Temporal Memory-Enhanced and Denoising Transformer for Surgical Instrument Segmentation

arXiv:2609.16797v1 Announce Type: new Abstract: Query-based segmentation methods have shown promising potential for surgical instrument segmentation and recognition, which is essential for scene under

Test-Time Unlearning via Sparse Autoencoder

arXiv:2609.16229v1 Announce Type: cross Abstract: Machine unlearning aims to remove specific knowledge from a trained large language model (LLM) without retraining from scratch. Existing methods modif

The Robot Data Factory

model-releasesarxiv-cs-ro

arXiv:2609.16705v1 Announce Type: new Abstract: Physical AI requires more than increasingly large robot datasets: intelligent robots acquire knowledge through continuous interaction with the physical

Unifying Semantic Priors and High-Frequency Traces: Enhancing V-JEPA with Mixture-of-Experts for Robust Synthetic Image Forensics

arXiv:2609.16778v1 Announce Type: new Abstract: The unchecked proliferation of manipulated images on social media platforms has increased the spread of misinformation, posing a severe threat to public

A Three-Axis Stress Test of LLM vs Classical ML for Network Intrusion Detection under Distribution Shift and Adversarial Evasion

arXiv:2609.13511v1 Announce Type: cross Abstract: Large language models are increasingly benchmarked against classical machine learning for network intrusion detection (NIDS), almost always using same

researcharxiv-cs-ai

Agents

Asclepius: An Adaptive Harness for Long-Horizon Clinical Agents

arXiv:2609.13543v1 Announce Type: new Abstract: LLM agents are predominantly benchmarked on short, single-task trajectories, yet real deployments run for hours under contention, surfacing a different

agentsarxiv-cs-ai

Beyond Generation and Accuracy: Diagnosing and Enhancing Visual Chain-of-Thought for Geometry Problem Solving

arXiv:2609.12606v2 Announce Type: replace Abstract: While multimodal reasoning has advanced rapidly, solving complex geometry problems critically hinges on active visual assistance, such as constructi

Beyond Natural Images: Rethinking AI-Generated Image Detection in Documents

arXiv:2609.14352v1 Announce Type: new Abstract: AI-generated image detection has attracted increasing attention, but existing evaluations mainly focus on natural images, leaving AI-generated document

Biquaternionic Space with Complex-valued Attention for Temporal Knowledge Graph Completion

arXiv:2609.14279v1 Announce Type: cross Abstract: Temporal knowledge graph embedding (TKGE) models infer missing facts in knowledge graphs that evolve over time. Many existing models use a single geom

BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents

arXiv:2609.12394v2 Announce Type: replace Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent ga

Bridging the Gap in ECG-Based Emotion Recognition: A Unified Evaluation of Deep Learning Models

model-releasesarxiv-cs-lg

arXiv:2609.15055v1 Announce Type: cross Abstract: Deep learning has led to numerous proposed architectures for Automated Emotion Recognition (AER) from electrocardiogram (ECG) data, but inconsistencie

CAL-MOS: Bridging Layers with Adapters for Robust MOS Prediction Across Speech Foundation Models

arXiv:2609.14956v1 Announce Type: cross Abstract: Speech Quality Assessment (SQA) is essential for modern speech technologies, and recent non-intrusive SQA predictors increasingly rely on Speech Found

Chemical and geometric representation fidelity improves drug--target affinity prediction

arXiv:2609.13230v1 Announce Type: cross Abstract: Predicting drug--target binding affinity (DTA) requires models to distinguish subtle chemical and structural determinants underlying molecular recogni

Agents

CoArena: Evaluating Computer-Use and Multi-Agent Systems in Real Time

arXiv:2609.14239v1 Announce Type: new Abstract: Static benchmarks for computer-use agents fix a task set at release and score every system against it once. That makes them reproducible, and it lets th

agentsarxiv-cs-lg

Diagnosing Faults in Reinforcement Learning Simulators and World Models with Canonical Polynomial Invariants

arXiv:2609.13194v1 Announce Type: cross Abstract: A large literature builds physical structure into learned dynamics on the premise that models respecting the underlying physics predict better. We tes