Search: “evaluation”

SurfSpec: Enhancing Off-Target-Agnostic Specificity by Bounding Pocket-Ligand Geometric Mismatch

arXiv:2609.02963v1 Announce Type: cross Abstract: Lead optimization in structure-based drug design aims to improve target binding while avoiding unintended interactions with off-target pockets. Howeve

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

TabScope: Question-Adaptive Scope Selection for Table Question Answering

DGX agent

arXiv:2609.03395v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on table question answering, yet their accuracy often degrades as table size increases. We

model-releasesarxiv-cs-ai

4 Sept 2026

The Blind Spot in 2D Infants' Pose Estimation:Robust Learning from Noisy Annotations

arXiv:2609.04009v1 Announce Type: cross Abstract: Noisy annotations pose a significant challenge for supervised deep learning, as neural networks rely on large-scale, high-quality labeled data whose c

researcharxiv-cs-ai

This work introduces diffusion-augmented LLMs, a new class of models. They first suggest that speculative decoding needs a separate draft mo…

This work introduces diffusion-augmented LLMs, a new class of models. They first suggest that speculative decoding needs a separate draft model. Diffusion LLMs give up the quality of the model they re

agentsdair-ai--x

Tutorials

TokenMatch: 3D Mesh Correspondence Transformer with Curvature-Guided Tokenisation

arXiv:2609.04202v1 Announce Type: new Abstract: While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-i

tutorialsarxiv-cs-cv

ToolDF: Tool-Integrated Reasoning for Mixed-Authenticity Audio Deepfake Detection

arXiv:2609.03620v1 Announce Type: cross Abstract: Audio deepfake detection is commonly formulated as clip-level binary classification of single-domain audio. However, real-world manipulated audio can

Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment

arXiv:2601.04736v2 Announce Type: replace Abstract: Despite remarkable capability in multi-modal understanding, deploying Multi-modal Large Language Models (MLLMs) in open-ended conversational scenari

Towards Numerical TOHTN Planning with SMT-based HTN-SAT Encoding

arXiv:2609.03938v1 Announce Type: new Abstract: While HTN planning has received significant attention in recent years, support for numerical reasoning remains very limited. In this paper, we investiga

TRACE: Spatiotemporal Contact Memory Graph Network Simulator for Granular Dynamics

model-releasesarxiv-cs-lg

arXiv:2609.02991v1 Announce Type: new Abstract: Learned graph simulators provide an efficient alternative to high-fidelity solvers for granular dynamics. However, granular motion depends strongly on i

TRaIL-Odom: Tightly Coupled Continuous Time Radar-IMU-LiDAR Odometry with Adaptive Doppler Weighting

arXiv:2609.03561v1 Announce Type: new Abstract: Existing radar-LiDAR fusion methods rely on fixed residual weights, even though the informativeness of radar Doppler and LiDAR geometry is scan- and dir

safetyarxiv-cs-ro

Translation as a Decision Space: A Multi-Agent Perspective on Low-Resource Dialect Generation

arXiv:2609.04048v1 Announce Type: cross Abstract: Neural machine translation (NMT) systems typically produce a single output per input, obscuring the alternative decision trajectories implicitly avail

agentsarxiv-cs-ai

Two-Stage Reinforcement Learning for Sound and Adversarial Test Generation in Code LLMs

arXiv:2609.03955v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially advanced code generation with large language models (LLMs) through executable feedback. The feedback for c

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

arXiv:2312.09454v3 Announce Type: replace-cross Abstract: Purpose: Uncertainty Quantification (UQ) has gained traction in an attempt to improve the interpretability and robustness of machine learning

Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

arXiv:2609.03729v1 Announce Type: new Abstract: Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the

Unlike other players in the OCR space, we don't block our competitors from accessing our platform. We're also fully committed towards open, …

model-releasesjerry-liu--x

Unlike other players in the OCR space, we don't block our competitors from accessing our platform. We're also fully committed towards open, reproducible benchmarks for document parsing and extraction

Virtual Testing of Automated Driving Systems through Credible Simulations

arXiv:2609.03760v1 Announce Type: new Abstract: Simulation is increasingly used to support safety-related decision-making in road transport, particularly for the assessment and approval of automated d

safetyarxiv-cs-ro

Local Ai

WeatherNext 3: Increasing resolution and performance of global weather models with raw observations

arXiv:2609.03582v1 Announce Type: new Abstract: State-of-the-art AI weather models have shown impressive medium-range forecast skill and computational efficiency, but suffer two key shortcomings: thei

local-aiarxiv-cs-lg

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

model-releasesarxiv-cs-cl

arXiv:2609.03254v1 Announce Type: new Abstract: Large Language Models (LLMs) often help users generate artifacts through iterative cycles of generation and revision in conversation. A challenge here i

What Matters for Aggressive Decoding-Time KV Eviction? Temporal Aggregation and Ranking Preservation

arXiv:2609.03515v1 Announce Type: new Abstract: Decoding-time KV cache compression research focuses heavily on designing better token scoring functions, while the temporal rule that aggregates scores

researcharxiv-cs-ai

WIDE: Wildcard Inference with Dynamic Expansion for Cross-Modal Generative Retrieval

arXiv:2609.03554v1 Announce Type: cross Abstract: Generative retrieval has demonstrated significant success by unifying representation learning and search into a single sequence-to-sequence generation

WorldReward: Reward Modeling for Camera-Conditioned World Models

arXiv:2609.03952v1 Announce Type: new Abstract: Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geomet

A Common Measure of Communication for Speech Brain-Computer Interfaces

arXiv:2609.02887v1 Announce Type: new Abstract: Speech brain-computer interfaces (speech BCIs) translate neural activity into language, offering a path towards restoring speech for people with paralys

A Layered Taxonomy for Chinese Learner Grammatical Error Annotation

arXiv:2609.02153v1 Announce Type: new Abstract: Grammatical error annotation in Chinese learner writing requires labels that are both consistent and linguistically meaningful. This paper proposes a la

researcharxiv-cs-cl

Applications

A Unified Particle Filter LSTM for Data-Driven Process Simulation

arXiv:2609.01967v1 Announce Type: new Abstract: Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model o

applicationsarxiv-cs-lg

A Unified Rate-Distortion Perspective on Vector, Product, and Scalar Quantization

arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding

Tutorials

Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method

arXiv:2408.02936v3 Announce Type: replace Abstract: Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires

tutorialsarxiv-cs-lg

Achieving Olympiad-Level Geometry Large Language Model Agent via Complexity Boosting Reinforcement Learning

arXiv:2512.10534v4 Announce Type: replace Abstract: Large language model (LLM) agents exhibit strong mathematical problem-solving abilities and can even solve International Mathematical Olympiad (IMO)

agentsarxiv-cs-ai

Action abstractions for amortized sampling

arXiv:2410.15184v2 Announce Type: replace-cross Abstract: As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignmen

safetyarxiv-cs-ai

Actor as Its Own Critic: Unifying Region Understanding and Localization via CycleGRPO

arXiv:2607.11581v2 Announce Type: replace Abstract: This paper introduces Actor as Its Own Critic, a unified reinforcement learning framework, Cycle Group Relative Policy Optimization (CycleGRPO), tha

AdaMem: Learning What to Remember with Adaptive Memory Policies for Personalized Agents

arXiv:2606.21144v2 Announce Type: replace-cross Abstract: Long-term memory systems allow LLM agents to preserve information beyond a single context window, but most systems focus on storing and retrie

Adversarial Stress Testing of Outlier Detection in Subjective Image Quality Assessment

arXiv:2509.06554v2 Announce Type: replace-cross Abstract: In subjective image and video quality assessment, observers rate or compare selected stimuli. Before calculating mean opinion scores (MOSs), u

AffectDelta: Beyond Emotion Labels for Image Editing

arXiv:2609.02616v1 Announce Type: new Abstract: Emotion-driven image editing aims to evoke a specified target emotion by modifying emotion-relevant visual cues in a source image, while preserving the

Agent Memory Is a Surface for Endogenous Authorization Laundering

arXiv:2609.01836v1 Announce Type: cross Abstract: Long-running LLM agents rely on persistent memory to carry state across interactions, including permissions, restrictions, and revocations. When memor

safetyarxiv-cs-ai

AI Contextual Measurement for Recovering Individual and Group-Level Effects: Validation Against Survey Measures and an Occupational Application

arXiv:2609.02821v1 Announce Type: new Abstract: Researchers increasingly use artificial intelligence to construct measures of social, organizational, and occupational characteristics that are absent f

researcharxiv-cs-ai

Allocate Before You Embed: Adaptive Visual Input Allocation for Video Embeddings

arXiv:2609.01778v1 Announce Type: new Abstract: Large-scale video retrieval requires embedding models to encode long and diverse videos under tight visual-input and inference budgets. Existing methods

Are Non-English Papers Reviewed Fairly? Language-of-Study Bias in NLP Peer Reviews

arXiv:2604.07119v2 Announce Type: replace Abstract: Peer review plays a central role in the NLP publication process, but is susceptible to various biases. Here, we study language-of-study (LoS) bias:

Astra achieves state-of-the-art results on Agents’ Last Exam, AutomationBench, and ScreenSpot Pro, benchmarks for computer workflow tasks ac…

OpenAI’s new language‑model system **Astra** has achieved state‑of‑the‑art performance on three key workflow benchmarks: the Agents’ Last Exam, AutomationBench, and ScreenSpot Pro. These suites evalua

model-releasesopenai--x

Asymmetric Paired-Annotation Learning for Multi-Structure ULF Pediatric Brain MRI Segmentation

arXiv:2609.02210v1 Announce Type: new Abstract: Portable ultra-low-field (ULF) MRI can expand access to pediatric neuroimaging, but segmentation at 0.064 T remains challenging because anatomical bound

researcharxiv-cs-cv

Before the Script, Set the Stage: How Worldview Simulation Amplifies Psychologically Grounded Persuasion in Multi-Turn Jailbreaking

arXiv:2609.02414v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks demonstrate that harmful intent can be distributed across dialogue, yet existing methods obscure what conversational mech

safetyarxiv-cs-ai

Benchmarking AI systems is a continual process that co-evolves with the models. New benchmarks challenge AI capabilities with emerging quest…

researchfrancois-chollet--x

Benchmarking AI systems is a continual process that co-evolves with the models. New benchmarks challenge AI capabilities with emerging questions to shape the directions and feedback signal of the rese

Best practices for building agentic automations with Amazon Quick Automate

Learn best practices for building production-grade, agent-based business process automations with Amazon Quick Automate: choosing the right process, designing focused agents, combining them with deter

agentsaws-ml-blog

Breaking the Geometric Bottleneck: Contrastive Expansion in Asymmetric Cross-Modal Distillation

arXiv:2603.06698v3 Announce Type: replace Abstract: Knowledge distillation between asymmetric architectures often induces severe geometric constraints on the learned representation space. We investiga

CA-OPD: Confidence-Aware On-Policy Distillation for Structured Visual Prediction

arXiv:2609.02401v1 Announce Type: new Abstract: Autoregressive vision language models unify heterogeneous perception tasks but are highly susceptible to compounding errors. On-policy distillation (OPD

CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning

arXiv:2609.02450v1 Announce Type: new Abstract: Semantic triggers in federated learning (FL) can be less conspicuous than synthetic patches, but sample-dependent placement may weaken backdoor implanta

CAPTURE: Disentangling Preference Drift from Memory Poisoning in Personalized LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.02265v1 Announce Type: new Abstract: Personalized language agents use persistent memory to adapt to users over time, but the same mechanism creates an attack surface. When new information c

CAT-Flow: Curvature-Adaptive sTeps for Flow Matching

arXiv:2609.01746v1 Announce Type: new Abstract: Flow Matching has emerged as a leading framework for generative modeling, powering state-of-the-art systems such as FLUX and Stable Diffusion 3.5. Howev

CHisAgent: A Multi-Agent Framework for Event Taxonomy Construction in Ancient Chinese Cultural Systems

arXiv:2601.05520v2 Announce Type: replace Abstract: Despite strong performance on many tasks, large language models (LLMs) show limited ability in historical and cultural reasoning, particularly in no

Cliff: Learning Process Rewards from the First Mistake

arXiv:2609.02817v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for large language model (LLM) post-training, but its reliance

safetyarxiv-cs-lg