18 papers
ArbiGraph: Arbitrarily Scalable Verifiable Task Graphs for Evaluating Context Management
Pavel Golikov, Evgenii Opryshko, Gennady Pekhimenko +1
We introduce ARBIGRAPH, a benchmark generator for evaluating whether tool-assisted language agents can retain, update, compose, and discard task-relevant context across extended re…
DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures
Peiming Yang, Sankeerth Durvasula, Ivan Fernandez +4
High-performance Host processors can integrate Processing-In-Memory (PIM) devices, which can accelerate memory-intensive kernels of Machine Learning (ML) models, including Large La…
SpecBench: Evaluating Specification-Level Reasoning for Software Engineering LLM Agents
Grant Hamblin, Kevin Song, Zhanda Zhu +4
Software engineering (SWE) agents are transitioning from code generation to full software development lifecycle automation. A critical phase in this lifecycle is specification desi…
SwiftFusion: Scalable Sequence Parallelism for Distributed Inference of Diffusion Transformers on GPUs
Jiacheng Yang, Jun Wu, Yaoyao Ding +3
Diffusion Transformers (DiTs) have gained increasing adoption in high-quality image and video generation. As demand for higher-resolution images and longer videos increases, single…
Robust Reasoning Benchmark
Pavel Golikov, Evgenii Opryshko, Gennady Pekhimenko +1
While Large Language Models (LLMs) achieve high performance on standard mathematical benchmarks, their problem-solving abilities depend on the context and textual formatting. We in…
DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling
Yubo Gao, Renbo Tu, Gennady Pekhimenko +1
Differentially-Private SGD (DP-SGD) and its adaptive variant DP-Adam are powerful techniques to protect user privacy when using sensitive data to train neural networks. During trai…