6 papers
MT-OSC: Path for LLMs that Get Lost in Multi-Turn Conversation
Jyotika Singh, Fang Tu, Miguel Ballesteros +6
Large language models (LLMs) suffer significant performance degradation when user instructions and context are distributed over multiple conversational turns, yet multi-turn (MT) i…
JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agents
Sandip Ghoshal, Anshul Mittal, Jyotika Singh +9
Large language model (LLM) agents augmented with external tools often struggle as number of tools grow large and become domain-specific. In such settings, ambiguous tool descriptio…
DiffuMask: Diffusion Language Model for Token-level Prompt Pruning
Caleb Zheng, Jyotika Singh, Fang Tu +6
In-Context Learning and Chain-of-Thought prompting improve reasoning in large language models (LLMs). These typically come at the cost of longer, more expensive prompts that may co…
Barriers to Discrete Reasoning with Transformers: A Survey Across Depth, Exactness, and Bandwidth
Michelle Yuan, Weiyi Sun, Amir H. Rezaeian +5
Transformers have become the foundational architecture for a broad spectrum of sequence modeling applications, underpinning state-of-the-art systems in natural language processing,…
Open Agent Specification (Agent Spec): A Unified Representation for AI Agents
Soufiane Amini, Yassine Benajiba, Cesare Bernardis +16
The proliferation of agent frameworks has led to fragmentation in how agents are defined, executed, and evaluated. Existing systems differ in their abstractions, data flow semantic…
Can LLMs Narrate Tabular Data? An Evaluation Framework for Natural Language Representations of Text-to-SQL System Outputs
Jyotika Singh, Weiyi Sun, Amit Agarwal +4
In modern industry systems like multi-turn chat agents, Text-to-SQL technology bridges natural language (NL) questions and database (DB) querying. The conversion of tabular DB resu…