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 storiesSol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation
Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration methods have…
RLM-Cascade: Response-Level Speculative Decoding for Cost-Efficient LLM API Serving
We present RLM-Cascade, a proxy-layer system that applies speculative decoding at the response level to reduce LLM API costs without requiring model architectur…
IndicGuard: A Multilingual Safety Guard Model and Dataset for Indic Languages
As Large Language Models (LLMs) achieve widespread integration across diverse linguistic landscapes, ensuring their safety and alignment with regional normative…
Rethinking Prototype-based Similarity Learning for Few-Shot Object Detection
Few-shot object detection aims to detect novel object categories from only a few labeled examples, avoiding costly large-scale annotation. Recent prototype-base…
Abstract representational geometry supports inference in large language models
A defining feature of human intelligence is the ability to adapt to changing environments by inferring latent task structure from sparse observations. Neuroscie…
Distribution-Aware Diffusion-LLM for Robust Ultra-Long-Term Time Series Forecasting
Time series forecasting is a fundamental machine learning task. Recent work has explored Large Language Models (LLMs) for this purpose due to their strong gener…
Quantum Convolutional Neural Networks for Groundwater Heat Plume Prediction: A Surrogate Modeling Approach
Quantum machine learning methods are increasingly explored for modeling complex environmental systems, including groundwater heat plume dynamics. In this work, …
Self-Compacting Language Model Agents
Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context w…
E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis
While Vision-Language Models (VLMs) show great promise in volumetric medical report generation, they frequently suffer from visual hallucinations and a lack of …
CAVEWOMAN: How Large Language Models Behave Under Linguistic Input and Output Compression
"Talk short. Drop grammar. Save token." This caveman style is widely promoted as a way to cut inference cost, but whether it actually saves anything depends on …
Zero-Shot Test-Time Canonicalization using Out-of-Distribution Scoring
Pretrained vision models often misclassify inputs that are rotated, scaled, or sheared, even though these affine transformations leave the object class unchange…
Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources
The increasing integration of distributed energy resources (DERs) is crucial for power system decarbonization, yet unlocking DERs' flexibility is challenged by …
MEMPROBE: Probing Long-Term Agent Memory via Hidden User-State Recovery
Long-term memory promises LLM agents that grow more capable across sessions, maintaining an accurate, evolving understanding of the user that interaction forms.…
SER: Learning to Ground Video Reasoning with Semantic Evidence Rewards
Video MLLMs often struggle with fine-grained spatio-temporal reasoning, sometimes generating correct answers based on irrelevant frames or objects. Although out…
Forget to Improve: On-Device LLM-Agent Continual Learning via Budget-Curated Memory
On-device language-model agents improve by accumulating experience in retrieved memory rather than by updating weights. This memory is hard-bounded and exposed:…
Variational Inference via Entropic Transport Descent
Particle-based variational inference (ParVI) methods approximate an intractable target distribution by evolving an ensemble of interacting samples. Existing app…
KidRisk: Benchmark Dataset for Children Dangerous Action Recognition
Children are naturally energetic, and during their spontaneous activities, they often encounter potentially dangerous situations, especially when lacking parent…
Supervised Post-training of Speech Foundation Models for Robust Adaptation in Speech Deepfake Detection
Large speech foundation models have shown strong potential for speech deepfake detection, but direct fine-tuning is limited by a mismatch between self-supervise…
Offline Multi-agent Continual Cooperation via Skill Partition and Reuse
Extracting skills from multi-agent offline dataset improves learning efficiency via sharing task-invariant coordination skills among tasks. In settings where ta…
TopoCast: A Topological Fidelity Framework for Evaluating Transformer-Based Time Series Forecasting
Deep learning-based models have achieved state-of-the-art performance in Time Series Forecasting (TSF), yet their evaluation remains dominated by pointwise erro…
C3-Bench: A Context-Aware Change Captioning Benchmark
While Change Captioning systems have garnered substantial attention to respond to our evolving world, their true performance on diverse real-world change contex…
Optimizing Abstractive Summarization With Fine-Tuned PEGASUS
Abstractive text summarization is the technique of generating a short and concise summary comprising the salient ideas of a source text without making a subset …
Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning
Cooperative multi-agent reinforcement learning assumes each agent shares the same reward function and can be trained effectively using the Trust Region framewor…
KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction
While WGS-based AMR prediction has reached high accuracy, existing models lack a mechanism to ground neural attributions in established biological pathways. We …
Pulmonary Embolism Risk Stratification from CTPA and Medical Records: Vascular Graphs Are Not All You Need
Risk stratification for pulmonary embolism (PE) is critical for clinical decision-making. Stratification guidelines are based on patient medical records, parame…
DualEval: Joint Model-Item Calibration for Unified LLM Evaluation
Current LLM evaluation relies on two complementary but often disconnected signals: static benchmarks with objective correctness labels and arena-style preferenc…
ProvenAI: Provenance-Native Traces of Evidence in Generated Answers
Retrieval-augmented systems routinely present citations alongside generated answers, yet a citation does not confirm that the corresponding source meaningfully …
scBench-Long: Verifiable Benchmarking of Long-Horizon Single-Cell Biology
Single-cell studies require analysts to convert raw measurements into specific biological claims through multi-step workflows and integration of metadata, assay…
Capacity-Controlled Multi-View Stylization of 3D Gaussian Splatting
While 3D Gaussian Splatting (3DGS) provides an efficient and explicit representation for novel view synthesis, enforcing stylistic coherence across viewpoints r…
Diagnosing Task Insensitivity in Language Agents
Large language models can serve as capable long-horizon agents, but their out-of-distribution (OOD) generalization remains weak. We identify a key source of thi…