Zobrazeno 1 - 10
of 12 672
pro vyhledávání: '"P. Shelby"'
Autor:
Ma, Zixian, Zhang, Jianguo, Liu, Zhiwei, Zhang, Jieyu, Tan, Juntao, Shu, Manli, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Xiong, Caiming, Krishna, Ranjay, Savarese, Silvio
While open-source multi-modal language models perform well on simple question answering tasks, they often fail on complex questions that require multiple capabilities, such as fine-grained recognition, visual grounding, and reasoning, and that demand
Externí odkaz:
http://arxiv.org/abs/2412.05479
Autor:
Kokane, Shirley, Zhu, Ming, Awalgaonkar, Tulika, Zhang, Jianguo, Hoang, Thai, Prabhakar, Akshara, Liu, Zuxin, Lan, Tian, Yang, Liangwei, Tan, Juntao, Murthy, Rithesh, Yao, Weiran, Liu, Zhiwei, Niebles, Juan Carlos, Wang, Huan, Heinecke, Shelby, Xiong, Caiming, Savarese, Silivo
Evaluating the output of Large Language Models (LLMs) is one of the most critical aspects of building a performant compound AI system. Since the output from LLMs propagate to downstream steps, identifying LLM errors is crucial to system performance.
Externí odkaz:
http://arxiv.org/abs/2411.13547
Autor:
Chen, Haolin, Feng, Yihao, Liu, Zuxin, Yao, Weiran, Prabhakar, Akshara, Heinecke, Shelby, Ho, Ricky, Mui, Phil, Savarese, Silvio, Xiong, Caiming, Wang, Huan
Large language models (LLMs) have shown impressive capabilities, but still struggle with complex reasoning tasks requiring multiple steps. While prompt-based methods like Chain-of-Thought (CoT) can improve LLM reasoning at inference time, optimizing
Externí odkaz:
http://arxiv.org/abs/2411.04282
Autor:
Liu, Zhiwei, Yao, Weiran, Zhang, Jianguo, Murthy, Rithesh, Yang, Liangwei, Liu, Zuxin, Lan, Tian, Zhu, Ming, Tan, Juntao, Kokane, Shirley, Hoang, Thai, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
We introduce the Principled Reasoning and Acting (PRAct) framework, a novel method for learning and enforcing action principles from trajectory data. Central to our approach is the use of text gradients from a reflection and optimization engine to de
Externí odkaz:
http://arxiv.org/abs/2410.18528
Autor:
Cox, Shelby, Makhlin, Igor
The type A cluster configuration space, commonly known as $\mathcal M_{0,n}$, is the very affine part of the binary geometry associated with the associahedron. The tropicalization of $\mathcal M_{0,n}$ can be realized as the space of phylogenetic tre
Externí odkaz:
http://arxiv.org/abs/2410.13652
Phylogenetic networks describe the evolution of a set of taxa for which reticulate events have occurred at some point in their evolutionary history. Of particular interest is when the evolutionary history between a set of just three taxa has a reticu
Externí odkaz:
http://arxiv.org/abs/2409.17894
Autor:
Bey, Sara, Fields, Shelby S., Combs, Nicholas G., Márkus, Bence G., Beke, Dávid, Wang, Jiashu, Ievlev, Anton V., Zhukovskyi, Maksym, Orlova, Tatyana, Forró, László, Bennett, Steven P., Liu, Xinyu, Assaf, Badih A.
The discovery of an anomalous Hall effect (AHE) sensitive to the magnetic state of antiferromagnets can trigger a new era of spintronics, if materials that host a tunable and strong AHE are identified. Altermagnets are a new class of materials that c
Externí odkaz:
http://arxiv.org/abs/2409.04567
Increasing use of large language models (LLMs) demand performant guardrails to ensure the safety of inputs and outputs of LLMs. When these safeguards are trained on imbalanced data, they can learn the societal biases. We present a light-weight, post-
Externí odkaz:
http://arxiv.org/abs/2409.13705
Autor:
Sprague, Jacob R., Larson, Shane L., Wang, Zhiyuan, Klomp, Shelby, Laeuger, Andrew, Winstone, George, Aggarwal, Nancy, Geraci, Andrew A., Kalogera, Vicky
Ultralight scalar fields can experience runaway `superradiant' amplification near spinning black holes, resulting in a macroscopic `axion cloud' which slowly dissipates via continuous monochromatic gravitational waves. For a particular range of boson
Externí odkaz:
http://arxiv.org/abs/2409.03714
Autor:
Zhang, Jianguo, Lan, Tian, Zhu, Ming, Liu, Zuxin, Hoang, Thai, Kokane, Shirley, Yao, Weiran, Tan, Juntao, Prabhakar, Akshara, Chen, Haolin, Liu, Zhiwei, Feng, Yihao, Awalgaonkar, Tulika, Murthy, Rithesh, Hu, Eric, Chen, Zeyuan, Xu, Ran, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing specialized models for agent tasks, driven by the scarcity of high-quality
Externí odkaz:
http://arxiv.org/abs/2409.03215