9 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…
GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations
Jyotika Singh, Fang Tu, Aziza Mirsaidova +11
Benchmarks like GSM8K are popular measures of mathematical reasoning, but leaderboard gains can overstate true capability due to memorization of fixed test sets. Most robustness va…
Do Image-Text Metrics Respect Semantic Invariances?
Amit Agarwal, Hitesh Laxmichand Patel, Meizhu Liu +9
Reference-free image-to-text evaluators are now standard for scoring image-caption alignment, yet it is unclear whether they respect semantic invariances. We present an invariance…
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,…