Zobrazeno 1 - 10
of 8 971
pro vyhledávání: '"ESKIN, A."'
We study the energy spectrum of three-particle systems (He-p-\mu), (He-d-\mu), (Li-p-\mu) and (Li-d-\mu) on the basis of variational approach with exponential and Gaussian basis. Using the Complex Coordinate Rotation (CCR) method we calculate energie
Externí odkaz:
http://arxiv.org/abs/2412.01507
We study hadronic light-by-light scattering contribution to the energy interval (1S-2S) in muonium. Various amplitudes of interaction of a muon and an electron are constructed, in which the effect of hadronic scattering of light-by-light is determine
Externí odkaz:
http://arxiv.org/abs/2411.09727
Large language models (LLMs) are susceptible to persuasion, which can pose risks when models are faced with an adversarial interlocutor. We take a first step towards defending models against persuasion while also arguing that defense against adversar
Externí odkaz:
http://arxiv.org/abs/2410.14596
The process of creating training data to teach models is currently driven by humans, who manually analyze model weaknesses and plan how to create data that improves a student model. Approaches using LLMs as annotators reduce human effort, but still r
Externí odkaz:
http://arxiv.org/abs/2410.06215
Reward Models (RMs) play a crucial role in aligning LLMs with human preferences, enhancing their performance by ranking outputs during inference or iterative training. However, the degree to which an RM generalizes to new tasks is often not known a p
Externí odkaz:
http://arxiv.org/abs/2410.01735
Autor:
Chen, Justin Chih-Yao, Prasad, Archiki, Saha, Swarnadeep, Stengel-Eskin, Elias, Bansal, Mohit
Large Language Models' (LLM) reasoning can be improved using test-time aggregation strategies, i.e., generating multiple samples and voting among generated samples. While these improve performance, they often reach a saturation point. Refinement offe
Externí odkaz:
http://arxiv.org/abs/2409.12147
Knowledge conflict arises from discrepancies between information in the context of a large language model (LLM) and the knowledge stored in its parameters. This can hurt performance when using standard decoding techniques, which tend to ignore the co
Externí odkaz:
http://arxiv.org/abs/2409.07394
Autor:
Saha, Swarnadeep, Prasad, Archiki, Chen, Justin Chih-Yao, Hase, Peter, Stengel-Eskin, Elias, Bansal, Mohit
Language models can be used to solve long-horizon planning problems in two distinct modes: a fast 'System-1' mode, directly generating plans without any explicit search or backtracking, and a slow 'System-2' mode, planning step-by-step by explicitly
Externí odkaz:
http://arxiv.org/abs/2407.14414
The model editing problem concerns how language models should learn new facts about the world over time. While empirical research on model editing has drawn widespread attention, the conceptual foundations of model editing remain shaky -- perhaps uns
Externí odkaz:
http://arxiv.org/abs/2406.19354
Vision-language models (VLMs) can respond to queries about images in many languages. However, beyond language, culture affects how we see things. For example, individuals from Western cultures focus more on the central figure in an image while indivi
Externí odkaz:
http://arxiv.org/abs/2406.11665