Search: “evaluation”

DSPO: Diversity-aware Subjective Policy Optimization for Robust Emotional Reasoning

arXiv:2609.36775v1 Announce Type: new Abstract: Reinforcement Learning has significantly advanced the complex reasoning capabilities of MLLMs. However, prevailing RL algorithms suffer a severe failure

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Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents

DGX agent

arXiv:2502.04492v3 Announce Type: replace Abstract: The advancement of LLMs and their accessibility have triggered renewed interest in multi-agent reinforcement learning as robust and adaptive framewo

safetyarxiv-cs-cl

30 Sept 2026

Efficient and Scalable Physics-Guided Fully Convolutional Spatiotemporal Learning for 3D Microstructure Evolution Prediction

arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r

local-aiarxiv-cs-lg

EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation

arXiv:2609.38046v1 Announce Type: new Abstract: Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with miss

safetyarxiv-cs-ro

Emergent Tonal Structure in Learned Chord Embeddings and Its Relation to Tonal Tension

arXiv:2609.36460v1 Announce Type: cross Abstract: Several tonal pitch spaces and computational models have been proposed to analyze tonal structure in Western tonal music, many of them grounded in pri

EmoRES-TTS: Residual-Enhanced Vector Steering for Emotional Speech Generation

arXiv:2609.38157v1 Announce Type: cross Abstract: Emotion-conditioned text-to-speech (TTS) models may fail to express the requested emotion reliably, and improving controllability by additional traini

researcharxiv-cs-cl

Encore: Few-Shot Agentic Discovery of Manipulation Strategies

arXiv:2609.37359v1 Announce Type: cross Abstract: Coding agents can now write, run, and debug programs with little human help. Robot tasks, however, are usually specified by a sentence that leaves out

EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory

arXiv:2609.37923v1 Announce Type: new Abstract: Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce Ep

agentsarxiv-cs-cv

Equally Good, Yet Different: Benchmarking Rashomon sets in AutoML packages

model-releasesarxiv-cs-lg

arXiv:2609.36970v1 Announce Type: new Abstract: The Rashomon effect describes the existence of multiple near-optimal models that achieve comparable performance while offering fundamentally different e

Estimation of Room Impulse Responses from Handclaps

arXiv:2609.35839v1 Announce Type: cross Abstract: Handclaps provide an equipment-free excitation for room acoustics, but their unknown and variable source waveform makes room impulse response (RIR) es

Event-Only Wingbeat Counting under Camera Motion: A Controlled MuJoCo Benchmark

arXiv:2609.37465v1 Announce Type: new Abstract: Counting completed wingbeats requires identifying individual cycles, including during frequency changes and pauses; estimating a dominant frequency alon

Evidence-Guided Schema Normalization for Temporal Tabular Reasoning

arXiv:2512.00329v2 Announce Type: replace-cross Abstract: Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose an approach that recasts the task

Evolving Towards Better Codes: LLM-Guided Search for High-Distance Binary Linear Codes

arXiv:2609.37056v1 Announce Type: cross Abstract: Evolutionary program search driven by large language models (LLMs) has produced record-breaking constructions for open problems in combinatorics and b

EvoMO-SR: Multiobjective LLM-based Evolution of Symbolic Expressions with substructure guidance

model-releasesarxiv-cs-lg

arXiv:2609.36187v1 Announce Type: new Abstract: Symbolic Regression (SR) is a data-driven method for scientific discovery which searches for interpretable analytical relationships within data. Recentl

ExceptionDrive: A Planning-Oriented Counterfactual Corner-Case Benchmark for Autonomous Driving

arXiv:2609.37871v1 Announce Type: cross Abstract: Average performance on routine driving benchmarks does not establish planner reliability under rare, safety-critical hazards. We proposed ExceptionDri

Hardware

Expanding AI Storage Access with NVIDIA cuObject and the NVIDIA SCADA Server SDK

NVIDIA has released its cuObject client and server libraries, providing RDMA‑based APIs that allow GPUs to access object storage directly without routing data through the host CPU. The xio‑sig consort

hardwarenvidia-developer

Explainable Machine Learning for Multilayer Planar Winding Inductance Estimation

model-releasesarxiv-cs-lg

arXiv:2609.37211v1 Announce Type: new Abstract: Rapid and accurate self-inductance estimation for multilayer rectangle-shaped planar windings is essential for modern high-frequency power converters, y

FairDiff: Mitigating the Self-Reinforcing Matthew Effect in Diffusion Recommender Models

arXiv:2609.36671v1 Announce Type: new Abstract: While the 'Matthew Effect' and filter bubbles are widely recognized outcome-level biases in recommender systems, we reveal that Diffusion Recommender Mo

Hardware

FastVR: Efficient Streaming Video Restoration with One-Step Diffusion

arXiv:2609.36757v1 Announce Type: new Abstract: Diffusion-based video restoration recovers realistic details, but its practical deployment is limited by two efficiency bottlenecks: costly VAE encoding

hardwarearxiv-cs-cv

FD-VAD: Semantic Endpoint Detection for Streaming Full-Duplex Speech

model-releasesarxiv-cs-cl

arXiv:2609.35791v1 Announce Type: new Abstract: Natural turn-taking in full-duplex voice interaction requires determining from partial speech whether a pause reflects hesitation or a completed convers

FigAct: Turning Scientific Figures into Active Canvases for Explanation

arXiv:2609.36190v1 Announce Type: new Abstract: Scientific figures are designed to communicate information visually, yet MLLMs typically explain them by translating their visual content back into text

FloCA: Towards Faithful and Logically Consistent Flowchart Reasoning

arXiv:2602.14035v2 Announce Type: replace Abstract: Flowchart-oriented dialogue (FOD) systems aim to guide users through multi-turn decision-making or operational procedures by following a domain-spec

agentsarxiv-cs-ai

FOCUS: Training-Free Decision-Preserving Context Compression for LLM Agents

arXiv:2609.37590v1 Announce Type: new Abstract: LLM agents accumulate interaction histories that grow linearly with task length, causing quadratic inference cost scaling and performance degradation fr

FocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution

arXiv:2609.36651v1 Announce Type: cross Abstract: Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by

local-aiarxiv-cs-ai

For anyone running local models and still guessing whether a prompt change helped

Running things locally already means you care more about control and reproducibility than most. Worth extending that to your prompts too. There's a live workshop on Oct 3 covering exactly that. Serj S

local-air-ollama

Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps

arXiv:2602.12624v2 Announce Type: replace-cross Abstract: Diffusion-based generative models have achieved remarkable performance across various domains, yet their practical deployment is often limited

researcharxiv-cs-cv

Foundation Neural-Network Quantum States for Molecular Potential Energy Surfaces in Second Quantization

arXiv:2609.37733v1 Announce Type: cross Abstract: Second-quantized neural-network quantum states have achieved accurate molecular energies, but extending them across molecular geometries requires a sh

safetyarxiv-cs-lg

FP2: Equipping Robotic Foundation Models with Force Control

arXiv:2609.37433v1 Announce Type: new Abstract: Robotic foundation models (RFMs) are increasingly capable of general-purpose manipulation, yet reliable physical interaction remains challenging in cont

safetyarxiv-cs-ro

FracGen: Learning How Objects Stretch and Tear with Physics-Informed Video Generation

arXiv:2609.38152v1 Announce Type: new Abstract: We introduce FracGen, a fracture-aware video generation model that produces plausible, controllable fracture dynamics from a single image of an intact o

From Laboratory to Real World: A New Benchmark Towards Privacy-Preserved Visible-Infrared Person Re-Identification

arXiv:2503.12232v3 Announce Type: replace Abstract: Aiming to match pedestrian images captured under varying lighting conditions, visible-infrared person re-identification (VI-ReID) has drawn intensiv

From Lexical Baselines to Agentic Retrieval-Augmented Generation: Structured Skill and Responsibility-Level Extraction with the SFIA Framework

arXiv:2609.35806v1 Announce Type: cross Abstract: Automated skill extraction underpins workforce planning, yet most systems represent skills as flat labels with no notion of the responsibility level a

agentsarxiv-cs-ai

From Surfaces to Volumes: Registered Geometry for Protein Representation Learning

arXiv:2609.36277v1 Announce Type: new Abstract: Existing protein geometry models typically represent molecular surfaces using local geometric features such as sampled points, normals, and curvature. W

local-aiarxiv-cs-ai

From Unity Simulation to Diffusion-Based Augmentation: Quantifying Dataset Balance for Robust Object Detection

arXiv:2609.38010v1 Announce Type: cross Abstract: Modern computer vision models achieve high accuracy when trained on large-scale annotated datasets. In critical domains such as construction safety mo

Generative Interactions: Weaving Multiparty Human Motion with Bilevel Latent Dynamics

arXiv:2609.37708v1 Announce Type: new Abstract: Human social behaviour is not a collection of independent motions, but a jointly organised process in which group dynamics and individual variation cont

GenoTrace: Inheritable Watermarks for Genome Foundation Model Distillation

arXiv:2609.35881v1 Announce Type: cross Abstract: Can a genome model retain a detectable record of the synthetic sequences used to train it? We study watermark inheritance through distillation with Ge

safetyarxiv-cs-lg

Geometry-Conditioned Fixed-Scaffold Encoders for Time-Warp Robust Sequence Retrieval

arXiv:2609.36809v1 Announce Type: new Abstract: Embedding-based retrieval is attractive for long sequence collections because each item can be encoded once and searched by nearest-neighbor ranking. Th

Geometry-Preserving Human-to-Robot Upper-Body Motion Retargeting from Monocular Video

model-releasesarxiv-cs-ro

arXiv:2609.37776v1 Announce Type: new Abstract: Monocular RGB video provides an accessible source of human demonstrations for upper-body robot motion, yet video-driven human-to-robot transfer remains

GLASS: Global Latent Aggregation with Slot-based Set Decoding for Scalable All-Atom Crystal Generation

arXiv:2609.37158v1 Announce Type: new Abstract: Generative models for crystals enable the discovery of novel structures, but scaling all-atom generation to larger systems such as metal--organic framew

researcharxiv-cs-lg

Godel Forest: Balancing Search Depth and Breadth for Data-Centric Recursive Self-Improvement

arXiv:2609.36675v1 Announce Type: new Abstract: Recursive self-improvement (RSI) aims to achieve compounding gains by having models improve themselves. While most existing RSI systems optimize externa

agentsarxiv-cs-cl

Graph-Conditioned On-Policy Agent Distillation from Off-the-Shelf Teachers

arXiv:2609.37522v1 Announce Type: new Abstract: On-policy distillation (OPD) trains compact language agents with teacher feedback on student-generated trajectories. In multi-turn tasks, compounding er

safetyarxiv-cs-lg

Graph neural networks for sampling-invariant embeddings of organized signal sets

arXiv:2609.35934v1 Announce Type: cross Abstract: Sensor networks and radars can deliver signals as organized sets, e.g. ordered signals, signals describing range cells within a grid or signals percei

Grounded Revision vs. Prior Injection: Probing Retrieval-Augmented Patent Claim Amendment

model-releasesarxiv-cs-cl

arXiv:2609.36550v1 Announce Type: new Abstract: Retrieval-augmented generation is widely used in professional writing, yet whether retrieval grounds revision or merely injects templates is rarely test

Industry

Half a million downloads in a month. Today, our open source family takes another step forward. Thank you for the incredible support behind o…

Half a million downloads in a month. Today, our open source family takes another step forward. Thank you for the incredible support behind our first-generation models. We’re excited to introduce TwIL-

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HandAnthro: Automated Hand Anthropometry from a Single Image

arXiv:2609.37855v1 Announce Type: cross Abstract: Hand anthropometry supports protective-glove design, but existing measurement methods often require trained operators, specialized hardware, or manual

HeadGuard: Selective Head Protection for Low-Bit VLM KV-Cache Quantization

arXiv:2609.35800v1 Announce Type: cross Abstract: Low-bit key-value (KV) cache quantization saves storage but can sharply degrade vision-language model (VLM) accuracy. We introduce HeadGuard, a compos

Hardware

HelixWorld: A Real-time Interactive Audio-Visual World Model

arXiv:2609.38123v1 Announce Type: new Abstract: World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time. Yet prevailing interactive world models r

hardwarearxiv-cs-cv

HiRAE: Hierarchical Representation Autoencoding with Residual Budgets

arXiv:2609.37775v1 Announce Type: cross Abstract: Pretrained visual representations support image generation, but may not fully preserve the fine-grained details needed for faithful reconstruction. Me

HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation

arXiv:2609.36559v1 Announce Type: cross Abstract: Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early