· ai
[Paper] In-Context Algebra
We investigate the mechanisms that arise when transformers are trained to solve arithmetic on sequences where tokens are variables whose meaning is determined o...
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- · ai
[Paper] Impacts of Racial Bias in Historical Training Data for News AI
AI technologies have rapidly moved into business and research applications that involve large text corpora, including computational journalism research and news...
- · ai
[Paper] Multimodal RewardBench 2: Evaluating Omni Reward Models for Interleaved Text and Image
Reward models (RMs) are essential for training large language models (LLMs), but remain underexplored for omni models that handle interleaved image and text seq...
- · software
[Paper] Checking the HAL Interface Specification Continuously, Right from the Start
The correct use of a Hardware Abstraction Layer (HAL) interface in embedded applications is crucial to prevent malfunctions, crashes, or even hardware damage. S...
- · ai
[Paper] LinkedOut: Linking World Knowledge Representation Out of Video LLM for Next-Generation Video Recommendation
Video Large Language Models (VLLMs) unlock world-knowledge-aware video understanding through pretraining on internet-scale data and have already shown promise o...
- · ai
[Paper] AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning
Equipping large language models (LLMs) with search engines via reinforcement learning (RL) has emerged as an effective approach for building search agents. Howe...
- · ai
[Paper] Cartesian-nj: Extending e3nn to Irreducible Cartesian Tensor Product and Contracion
Equivariant atomistic machine learning models have brought substantial gains in both extrapolation capability and predictive accuracy. Depending on the basis of...
- · ai
[Paper] PolaRiS: Scalable Real-to-Sim Evaluations for Generalist Robot Policies
A significant challenge for robot learning research is our ability to accurately measure and compare the performance of robot policies. Benchmarking in robotics...
- · ai
[Paper] Training Together, Diagnosing Better: Federated Learning for Collagen VI-Related Dystrophies
The application of Machine Learning (ML) to the diagnosis of rare diseases, such as collagen VI-related dystrophies (COL6-RD), is fundamentally limited by the s...
- · ai
[Paper] On the Universal Representation Property of Spiking Neural Networks
Inspired by biology, spiking neural networks (SNNs) process information via discrete spikes over time, offering an energy-efficient alternative to the classical...
- · ai
[Paper] LLMCache: Layer-Wise Caching Strategies for Accelerated Reuse in Transformer Inference
Transformer-based language models have achieved remarkable performance across a wide range of tasks, yet their high inference latency poses a significant challe...
- · ai
[Paper] What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels
Prosody -- the melody of speech -- conveys critical information often not captured by the words or text of a message. In this paper, we propose an information-t...