Research
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Latest in Research
30 storiesLearning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards
Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative methods such as G…
Reinforcement Learning Foundation Models Should Already Be A Thing
Foundation models for language and vision are powered by internet-scale data, while structured domains (tabular prediction, time-series forecasting, graph learn…
Learning from Your Own Mistakes: Constructing Learnable Micro-Reflective Trajectories for Self-Distillation
Self-distillation improves reasoning in large language models by using the model's own rollouts as training signal, typically through implicit logit-level align…
Scaling Learning-based AEB with Massive Unlabeled Data
This paper studies how to scale learning-based automatic emergency braking (AEB) with massive unlabeled fleet data under production constraints. Our approach is…
SAGE: Stochastic Prompt Optimization via Agent-Guided Exploration
Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients do not functio…
SciRisk-Bench: A Risk-Dimension-Aware Benchmark for AI4Science Safety
Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature analysis to l…
SenFlow: Inter-Sentence Flow Modeling for AI-Generated Text Detection in Hybrid Documents
Sentence-level AI-generated text detection (S-AGTD) for hybrid documents, where humans and LLMs co-author one text, faces two gaps: existing methods classify ea…
Be Your Own Teacher: Steering Protein Language Models via Unsupervised Reward Optimization
Protein language models (PLMs) have emerged as powerful tools for controllable biomolecular design, yet their post-training adaptation typically relies on costl…
A Controlled Benchmark of Quantum-Latent GAN Augmentation for Brain MRI
Medical image classification is often constrained by limited labeled data, motivating generative augmentation; recently, quantum generative models have been pro…
FOSC-X: An Extended Framework for Optimal Local Cuts and Non-Horizontal Cluster Selection from Clustering Hierarchies
Extracting a flat clustering solution from a hierarchy is a common task in practical cluster analysis and can be formulated as an optimisation problem. Existing…
Visual-OPSD: Cross-Modal On-Policy Self-Distillation for Efficient Unified Multimodal Reasoning
Unified multimodal models (UMMs) interleave generated ''visual thoughts'' (VTs) with text reasoning to improve spatial tasks. This incurs roughly an order-of-ma…
G-IdiomAlign: A Gloss-Pivoted Benchmark for Cross-Lingual Idiom Alignment
Idioms are difficult to transfer across languages due to their non-compositionality and weak surface-form grounding, making literal mappings unreliable. We pres…
Lifecycle-Aware Dynamic Analysis for Secure ML Model Execution
The growing reliance on pre-trained Machine Learning (ML) models has introduced new attack surfaces. Recent vulnerabilities demonstrate that malicious behavior …
Which Sections of a Research Paper Best Reveal Its Research Methods? Evidence from Library and Information Science
Research methods are essential carriers of knowledge contribution in academic papers. Automatic multi-label classification of research methods can support knowl…
Structure Over Nonlinearity: Explicit Interaction Architectures for Dynamical Learning
Most learning architectures for dynamical systems rely on generic nonlinear function approximation, often requiring high model complexity to capture structured …
Smoothness-Based Derandomization of PAC-Bayes Bounds
We study PAC-Bayes derandomization for smooth loss functions. Our goal is to obtain generalization bounds that hold with high probability for deterministic pred…
JourneyFormer: Encoding Airbnb Guest Journey with Sequence Modeling
Sequence modeling has become increasingly popular in recommendation and ranking algorithms, owing to its capacity to model users' historical behaviors and infer…
Towards an Agent-First Web: Redesigning the Web for AI Agents
The World Wide Web was built on an assumption held for three decades: the primary consumer of web content is a human being. This permeates every layer; its acce…
Giskard : Byzantine Robust and Confidential Aggregation for Large-Scale Decentralized Learning
Dealing simultaneously with confidentiality and Byzantine behaviors in decentralized learning is a challenging problem. Indeed, in decentralized learning, clien…
On Local Population-Risk Certificates
This paper develops local certificates for population-risk increments around a current model. For a local candidate set \(\mathcal D\), the certificate is a two…
AdsMind: A Physics-Grounded Multi-Agent System for Self-Correcting Discovery of Adsorption Configurations on Heterogeneous Catalyst Surfaces
Identifying the lowest-energy surface-adsorbate configuration is critical for modeling heterogeneous catalysis, yet exhaustive exploration with ab initio calcul…
IndicContextEval: A Benchmark for Evaluating Context Utilisation in Audio Large Language Models Across 8 Indic Languages
AudioLLMs enable speech recognition conditioned on textual prompts such as domain descriptions or entity lists. However, it remains unclear whether these models…
Dango: A Strictly L1-Only Large Language Model for Studying Second Language Acquisition
We introduce Dango, a 1.8B-parameter large language model designed for controlled studies of L1-to-L2 (Japanese-to-English) transfer in second language acquisit…
Generalised Eigenvalue Geometry of Semantic Adversarial Attacks
Recent empirical work shows that semantically equivalent paraphrases can fool financial sentiment classifiers: although a paraphrase remains close to the origin…
Machine Unlearning for the XGBoost Model with Network Intrusion Datasets
Machine Unlearning (MU) has emerged as an important technique for removing specific data points from trained models without requiring full retraining. However, …
Mechanism-Guided Selective Unlearning for RLVR-Induced Reasoning
We propose MAST (Mechanism-Aligned Selective Targeting), a mechanism-guided method for unlearning RLVR-induced reasoning with substantially lower collateral dam…
A Human-in-the-Loop Bayesian Optimization Framework for Constraint-Aware Bioprocess Development
This work presents an extension to Pareto Front Guided Sampling (PFGS), a Human-in-the-Loop (HitL) Bayesian Optimization (BO) framework in which Gaussian proces…
Transformer Geometry Observatory TGO-I: Spectral Geometry Observatory
Despite the widespread adoption of Vision Transformers (ViTs) and their success across numerous computer vision applications, the fundamental understanding of t…
Enhancing Decision-Making with Large Language Models through Multi-Agent Fictitious Play
Large language model (LLM)-based multi-agent systems (MAS) have demonstrated great potential in solving tasks with execution complexity, by distributing subtask…
Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation
Enhancing the formal math reasoning capabilities of Large Language Models (LLMs) has become a key focus in both mathematical and computer science communities in…