36 citations · 57 across the 6 of their papers we have counts for
6 papers
Controllable Text Generation for Large Language Models: A Survey
Xun Liang, Hanyu Wang, Yezhaohui Wang +8
In Natural Language Processing (NLP), Large Language Models (LLMs) have demonstrated high text generation quality. However, in real-world applications, LLMs must meet increasingly…
-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
Shunyu Yao, Noah Shinn, Pedram Razavi +1
Existing benchmarks do not test language agents on their interaction with human users or ability to follow domain-specific rules, both of which are vital for deploying them in real…
Can Language Models Solve Olympiad Programming?
Quan Shi, Michael Tang, Karthik Narasimhan +1
Computing olympiads contain some of the most challenging problems for humans, requiring complex algorithmic reasoning, puzzle solving, in addition to generating efficient code. How…
FireAct: Toward Language Agent Fine-tuning
Baian Chen, Chang Shu, Ehsan Shareghi +3
Recent efforts have augmented language models (LMs) with external tools or environments, leading to the development of language agents that can reason and act. However, most of the…
Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve
R. Thomas McCoy, Shunyu Yao, Dan Friedman +2
The widespread adoption of large language models (LLMs) makes it important to recognize their strengths and limitations. We argue that in order to develop a holistic understanding…
Understanding and Optimizing Serverless Workloads in CXL-Enabled Tiered Memory
Yuze Li, Shunyu Yao
Recent Serverless workloads tend to be largescaled/CPU-memory intensive, such as DL, graph applications, that require dynamic memory-to-compute resources provisioning. Meanwhile, r…