4 citations · 21 across the 53 of their papers we have counts for
14 papers · 1 filter
When Successful Strategies Fail: Adaptation to Environmental Novelty in Terminal Agents
Janvijay Singh, Vaishnavi Shrivastava, Dilek Hakkani-Tur +2
LLM agents increasingly solve long-horizon tasks by autonomously interacting with their environment. In doing so, their strategies rely on assumptions about that environment: which…
PlanBench-XL: Evaluating Long-Horizon Planning of LLM Tool-Use Agents in Large-Scale Tool Ecosystems
Jiayu Liu, Qihan Lin, Cheng Qian +8
LLM agents increasingly operate in large tool ecosystems, where real-world tasks require discovering relevant tools, inferring implicit sub-goals, and adapting to dynamic environme…
When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction
Vardhan Dongre, Joseph Hsieh, Viet Dac Lai +3
Large language models can follow complex instructions in a single turn, yet over long multi-turn interactions they often lose the thread of instructions, persona, and rules. This d…
Current Agents Fail to Leverage World Model as Tool for Foresight
Cheng Qian, Emre Can Acikgoz, Bingxuan Li +8
Agents built on vision-language models increasingly face tasks that demand anticipating future states rather than relying on short-horizon reasoning. Generative world models offer…
MultiSessionCollab: Learning User Preferences with Memory to Improve Long-Term Collaboration
Shuhaib Mehri, Priyanka Kargupta, Tal August +1
As conversational agents accumulate experience collaborating with users, adapting to user preferences is essential for fostering long-term relationships and improving collaboration…
SpeakRL: Synergizing Reasoning, Speaking, and Acting in Language Models with Reinforcement Learning
Emre Can Acikgoz, Jinoh Oh, Jie Hao +7
Effective human-agent collaboration is increasingly prevalent in real-world applications. Current trends in such collaborations are predominantly unidirectional, with users providi…
MAC: A Multi-Agent Framework for Interactive User Clarification in Multi-turn Conversations
Emre Can Acikgoz, Jinoh Oh, Joo Hyuk Jeon +7
Conversational agents often encounter ambiguous user requests, requiring an effective clarification to successfully complete tasks. While recent advancements in real-world applicat…
Measuring Combinatorial Creativity in Large Language Models and Humans
Samuel Schapiro, Sumuk Shashidhar, Akshay K. Jagadish +11
Combinatorial creativity, the process of combining familiar ideas in unfamiliar ways, is one of the foremost engines of scientific, technological, and artistic progress. This work…
Plan Verification for LLM-Based Embodied Task Completion Agents
Ananth Hariharan, Vardhan Dongre, Dilek Hakkani-Tür +1
Large language model (LLM) based task plans and corresponding human demonstrations for embodied AI may be noisy, with unnecessary actions, redundant navigation, and logical errors…
Spark: A System for Scientifically Creative Idea Generation
Aishik Sanyal, Samuel Schapiro, Sumuk Shashidhar +3
Recently, large language models (LLMs) have shown promising abilities to generate novel research ideas in science, a direction which coincides with many foundational principles in…
A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
Emre Can Acikgoz, Cheng Qian, Hongru Wang +5
Recent advances in Large Language Models (LLMs) have propelled conversational AI from traditional dialogue systems into sophisticated agents capable of autonomous actions, contextu…
Can a Single Model Master Both Multi-turn Conversations and Tool Use? CoALM: A Unified Conversational Agentic Language Model
Emre Can Acikgoz, Jeremiah Greer, Akul Datta +6
Large Language Models (LLMs) with API-calling capabilities enabled building effective Language Agents (LA), while also revolutionizing the conventional task-oriented dialogue (TOD)…
SMART: Self-Aware Agent for Tool Overuse Mitigation
Cheng Qian, Emre Can Acikgoz, Hongru Wang +5
Current Large Language Model (LLM) agents demonstrate strong reasoning and tool use capabilities, but often lack self-awareness, failing to balance these approaches effectively. Th…
Infogent: An Agent-Based Framework for Web Information Aggregation
Revanth Gangi Reddy, Sagnik Mukherjee, Jeonghwan Kim +3
Despite seemingly performant web agents on the task-completion benchmarks, most existing methods evaluate the agents based on a presupposition: the web navigation task consists of…